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J. Shukla

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J. Shukla

Abstract

We have attempted to determine the theoretical upper limit of dynamical predictability of monthly means for prescribed nonfluctuating external forcings. We have extended the concept of “classical” predictability, which primarily refers to the lack of predictability due mainly to the instabilities of synoptic-scale disturbances, to the predictability of time averages, which are determined by the predictability of low-frequency planetary waves. We have carded out 60-day integrations of a global general circulation model with nine different initial conditions but identical boundary conditions of sea surface temperature, snow, sea ice and soil moisture. Three of these initial conditions are the observed atmospheric conditions on 1 January of 1975, 1976 and 1977. The other six initial conditions are obtained by superimposing over the observed initial conditions a random perturbation comparable to the errors of observation. The root-mean-square (rms) error of random perturbations at all the grid points and all the model levels is 3 m s−1 in u and v components of wind. The rms vector wind error between the observed initial conditions is >15 m s−1.

It is hypothesized that for a given averaging period, if the rms error among the time averages predicted from largely different initial conditions becomes comparable to the rms error among the time averages predicted from randomly perturbed initial conditions, the time averages are dynamically unpredictable. We have carried out the analysis of variance to compare the variability, among the three groups, due to largely different initial conditions, and within each group due to random perturbations.

It is found that the variances among the first 30-day means, predicted from largely different initial conditions, are significantly different from the variances due to random perturbations in the initial conditions, whereas the variances among 30-day means for days 31–60 are not distinguishable from the variances due to random initial perturbations. The 30-day means for days 16–46 over certain areas are also significantly different from the valances due to random perturbations.

These results suggest that the evolution of long waves remains sufficiently predictable at least up to one month, and possibly up to 45 days, so that the combined effects of their own nonpredictability and their depredictabilization by synoptic-scale instabilities is not large enough to degrade the dynamical prediction of monthly means. The Northern Hemisphere appears to be more predictable than the Southern Hemisphere.

It is noteworthy that the lack of predictability for the second month is not because the model simulations relax to the same model state but because of very large departures in the simulated model states. This suggests that, with improvements in model resolution and physical parameterizations, there is potential for extending the predictability of time averages even beyond one month.

Here, we have examined only the dynamical predictability, because the boundary conditions are identical in all the integrations. Based on these results, and the possibility of additional predictability due to the influence of persistent anomalies of sea surface temperature, sea ice, snow and soil moisture, it is suggested that there is sufficient physical basis to undertake a systematic program to establish the feasibility of predicting monthly means by numerical integrations of realistic dynamical models.

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J. Shukla

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J. Shukla

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The global general circulation model of the Geophysical Fluid Dynamics Laboratory has been integrated with and without a cold sea surface temperature (SST) anomaly over the Somali coast and the western Arabian Sea. The temperature anomaly is −3°C near the Somali coast and linearly decreases eastward having zero anomaly at about 1500 km east of the coast. Comparison of the mean of the two model states indicates that the rainfall over India and the adjoining region is drastically reduced due to the colder SST anomaly over the western Arabian Sea. The other associated features due to the cold anomaly are an increase in sea surface pressure over the Arabian Sea, a decrease in local evaporation, and a reduction in the cross equatorial component of the wind at the surface and hence a reduction in the cross equatorial moisture flux. Statistical analysis of the results has been done by comparing the difference between the two mean states (“signal”) and the standard deviation of the errors (“noise”) in estimating the mean due to the finiteness of the averaging period. It is found that the results of the present numerical experiment are statistically significant.

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J. Shukla

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A combined CISK-barotropic-baroclinic instability analysis of the observed monsoon flow has been performed using the quasi-equilibrium assumption for the parameterization of moist convection. Linear perturbation equations for a three-layer quasi-geostrophic model are numerically integrated to get the most unstable mode. A deep cloud model, in which the height of the base of the cloud does not change with time and entrainment occurs for the whole depth of the cloud but detrainment occurs only at the top, is used to parameterize the effects of moist convection.

It is found that the maximum growth rate occurs for the smallest scales. The mechanism for scale selection is therefore not clear. The structure and energetics of the computed linear perturbations for a wavelength corresponding to that of the observed monsoon depressions is compared with the observations. The dominant energy transformation for the computed and the observed perturbations is found to be from eddy available potential energy to eddy kinetic energy. The primary source of heating is condensational heating. Reasonable agreements between the structure and the energetics of the computed perturbations and the observed monsoon depressions suggest that CISK may provide the primary driving mechanism for the growth of monsoon depressions.

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Paulo Nobre
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J. Shukla

Abstract

Empirical orthogonal functions (E0Fs) and composite analyses are used to investigate the development of sea surface temperature (SST) anomaly patterns over the tropical Atlantic. The evolution of large-scale rainfall anomaly patterns over the equatorial Atlantic and South America are also investigated. The EOF analyses revealed that a pattern of anomalous SST and wind stress asymmetric relative to the equator is the dominant mode of interannual and longer variability over the tropical Atlantic. The most important findings of this study are as follows.

Atmospheric circulation anomalies precede the development of basinwide anomalous SST patterns over the tropical Atlantic. Anomalous SST originate off the African coast simultaneously with atmospheric circulation anomalies and expand westward afterward. The time lag between wind stress relaxation (strengthening) and maximum SST warming (cooling) is about two months.

Anomalous atmospheric circulation patterns over northern tropical Atlantic are phase locked to the seasonal cycle. Composite fields of SLP and wind stress over northern tropical Atlantic can be distinguished from random only within a few months preceding the March–May (MAM) season. Observational evidence is presented to show that the El Niño–Southern Oscillation phenomenon in the Pacific influences atmospheric circulation and SST anomalies over northern tropical Atlantic through atmospheric teleconnection patterns into higher latitudes of the Northern Hemisphere.

The well-known droughts over northeastern Brazil (Nordeste) are a local manifestation of a much larger-scale rainfall anomaly pattern encompassing the whole equatorial Atlantic and Amazon region. Negative rainfall anomalies to the south of the equator during MAM, which is the rainy season for the Nordeste region, are related to an early withdrawal of the intertropical convergence zone toward the warm SST anomalies over the northern tropical Atlantic. Also, it is shown that precipitation anomalies over southern and northern parts of the Nordeste are out of phase: drought years over the northern Nordeste are commonly preceded by wetter years over the southern Nordeste, and vice versa.

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Bohua Huang
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J. Shukla

Abstract

Two sets of monthly sea surface wind stress over the tropical Atlantic Ocean are compared. The datasets are based on the ECMWF analyses during 1980–87 (the E-winds) and the monthly pseudo-wind stress from ship observations for the same period (the S-winds). Our examination shows that both datasets give qualitatively similar mean fields and annual cycles. Quantitatively, the zonal component of the E-winds is larger than that of the S-winds, especially in the winter hemisphere. The strongest southeast trades of the E-winds are also shifted to the east of the strongest southeast trades of the S-winds. In the vicinity of the ITCZ, the E-winds are more zonally oriented so that the convergence zone is not as clearly defined.

Interannually, both datasets show that the northeast trades were gradually strengthening from 1980 to 1986. The southeast trade winds, on the other hand, were anomalously strong during 1981–83, but weak during 1984–86. With the E-winds, the southeast trades decreased gradually during 1981–84, and with the S-winds, the southeast trades are maintained until late 1983, followed by a rapid weakening. In comparison with the E-winds, the S-winds interannual fluctuations over the central and eastern part of the tropical south and equatorial Atlantic are weak.

The sensitivity of an ocean general circulation model to the uncertainty of surface wind forcing as exemplified by these two datasets is examined. It is found that the systematic errors in the mean state and annual cycle of the model simulated sea surface temperature (SST) and upper ocean heat content (HC) are not sensitive to the differences in wind forcings. On the other hand, significantly different fluctuations of both the SSTs and the HCs on interannual timescales are generated by the simulations forced with the two wind data, respectively. A comparison between the observed and simulated SST anomalies shows that both simulations are reasonably close to the observations in the tropical north Atlantic Ocean. In the tropical south Atlantic, the E-winds produce a better simulation of the SST anomalies. Especially, the gradual weakening of the E-winds during 1981–84 produces an SST tendency consistent with observations, which are not shown in the S-winds simulation. However, the E-winds anomalies are poor during 1980–81 as judged by the comparison between the simulated and the observed SST anomalies.

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Bohua Huang
and
J. Shukla

Abstract

A numerical simulation has been conducted using a general circulation model of the tropical Atlantic Ocean forced with observed monthly surface wind stress for 1964–87 and parameterized surface heat flux. The simulated sea surface temperature (SST) and upper-ocean heat content (HC) are used to examine the low-frequency variability in the ocean. A comparison with the SST observations shows that the model realistically simulates the major features of the decadal variability at the sea surface, such as the fluctuation of the SST dipole pattern (or the meridional gradient). It also produces interannual variations with timescales of two to three years.

The simulated HC anomalies are used to examine the variations of the thermocline depth and the effects of ocean dynamics. A principal oscillation pattern (POP) analysis is performed to distinguish the spatial structures of decadal and interannual variations. It is found that the interannual variations are associated with tropical oceanic waves, stimulated by the fluctuations of the equatorial easterlies, which propagate eastward along the equator and westward to the north and south, resulting in an essentially symmetric structure about the equator at these scales. The periods of these modes are determined by the meridional width of the equatorial wind anomaly. The decadal mode, however, is associated with the ocean’s adjustment in response to a basinwide out-of-phase fluctuation between the northeast and southeast trade winds. For instance, forced by a weakening of the northeast winds and a simultaneous strengthening of the southeast winds, the thermocline deepens in a belt extending from 5°N in the west to the North African coast. At the same time, the thermocline shoals from the southeast coast to the equatorial ocean. The associated SST pattern exhibits a strong dipole structure with positive anomalies in the north and negative anomalies in the south. When the wind anomalies weaken, the warm water accumulated in the northern tropical ocean is released and redistributed within the basin. At this stage, the SST dipole disappears. In the framework of this separation of the variability into two dominant timescales, the extraordinarily large warm SST anomalies in the southeast ocean in the boreal summer of 1984 are a result of in-phase interference of the decadal and interannual modes.

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Timothy DelSole
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J. Shukla
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V. Krishnamurthy
and
J. Shukla

Abstract

A gridded daily rainfall dataset prepared from observations at 3700 stations is used to analyze the intraseasonal and interannual variability of the summer monsoon rainfall over India. It is found that the major drought years are characterized by large-scale negative rainfall anomalies covering nearly all of India and persisting for the entire monsoon season. The intraseasonal variability of rainfall during a monsoon season is characterized by the occurrence of active and break phases. During the active phase, the rainfall is above normal over central India and below normal over northern India (foothills of the Himalaya) and southern India. This pattern is reversed during the break phase.

It is found that the nature of the intraseasonal variability is not different during the years of major droughts or major floods. This suggests that a simple conceptual model to explain the interannual variability of the Indian monsoon rainfall should consist of a linear combination of a large-scale persistent seasonal mean component and a statistical average of intraseasonal variations. The large-scale persistent component can be part of low-frequency components of the coupled ocean–land–atmosphere system including influences of sea surface temperature, snow, etc. The mechanisms responsible for the intraseasonal variations are not well understood. This simple conceptual framework suggests that the ability to predict the seasonal mean rainfall over India will depend on the relative contributions of the externally forced component and the intraseasonal component. To the extent that the intraseasonal component is intrinsically unpredictable, success in long-range forecasting will largely depend on accurate quantitative estimates of the externally forced component.

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