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J. Shukla

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J. Shukla

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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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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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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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Timothy DelSole and J. Shukla
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J. Shukla and Y. Sud

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The General Circulation Model (GCM) of the Goddard Laboratory for Atmospheric Sciences (GLAS) was integrated for 107 days starting from the initial conditions of 15 May. In this experiment the clouds dynamically generated by the model affect the radiative heating fields continuously. Starting from the initial conditions valid for day 76 of this run, another integration was made for 31 days in which the clouds were specified on certain grid points, remaining fixed during the period of integration. The spatial distribution of the fixed clouds was such that the aggregate cloud frequency for a vertical level and each latitude circle remained the same as in each control run, and the highest cloud frequency grid points were assigned the cloudiness of 100%. The 31-day mean simulation of the second run (fixed clouds) is compared with the last 31-day mean simulation of the first run to study the effects of cloud-radiation feed- back on the mean monthly circulation, atmospheric energy cycle and the hydrological cycle, evaporation and precipitation and the local climate.

Results from these experiments show significant changes in the simulated large-scale dynamical circulation of the global model. Fixed clouds acting as zonally asymmetric radiative heat sources increase the generation of eddy available potential energy (EAPE) and its conversion to eddy kinetic energy. Generation of EAPE by net radiative heating increased by 50%(0.11 W m−2) for the fixed cloud experiment. The increase due to the stationary component was much larger (∼100%) but it was partially compensated by decrease due to the transient component. A substantial increase was found in the variances of the planetary-scale stationary waves and the medium-scale waves (wavenumber 6–10) of 2–7 day period. Although the sea surface temperatures were prescribed identically in both integrations, the changes in evaporation and precipitation were found to be much larger over the oceans compared to those over the land. We suspect that this happens because the ground temperature is determined by the model's beat balance at the earth's surface and therefore internal model feedbacks do not allow the hydrologic cycle over land to be very different between the fixed cloud run and the control run. Based on these calculations, we infer that cloud-radiation feedback is an important mechanism in the general circulation of the model atmosphere. It must be adequately parameterized in numerical experiments designed to simulate the mean climate and/or to examine the sensitivity of GCM's to changes in external boundary conditions or internal atmospheric constituents (such as aerosols and CO2) and their feedback effects.

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Paulo Nobre and J. Shukla

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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 and J. Shukla

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A 110-yr simulation is conducted using a specially designed coupled ocean–atmosphere general circulation model that only allows air–sea interaction over the Atlantic Ocean within 30°S–60°N. Since the influence from the Pacific El Niño–Southern Oscillation (ENSO) over the Atlantic is removed in this run, it provides a better view of the extratropical influences on the tropical air–sea interaction within the Atlantic sector. The model results are compared with the observations that also have their ENSO components subtracted.

The model reproduces the two major anomalous patterns of the sea surface temperature (SST) in the southern subtropical Atlantic (SSA) and the northern tropical Atlantic (NTA) Ocean. The SSA pattern is phase locked to the annual cycle. Its enhancement in austral summer is associated with atmospheric disturbances from the South Atlantic during late austral spring. The extratropical atmospheric disturbances induce anomalous trade winds and surface heat fluxes in its northern flank, which generate SST anomalies in the subtropics during austral summer. The forced SST anomalies then change the local sea level pressure and winds, which in turn affect the northward shift of the atmospheric disturbance and cause further SST changes in the deep Tropics during austral fall.

The NTA pattern is significant throughout a year. Like the SSA pattern, the NTA pattern in boreal winter–spring is usually associated with the heat flux change caused by extratropical atmospheric disturbances, such as the North Atlantic Oscillation. The SST anomalies then feed back with the tropical atmosphere and expand equatorward. From summer to fall, however, the NTA SST anomalies are likely to persist within the subtropics for more than one season after it is generated. Our model results suggest that this feature is associated with a local feedback between the NTA SST anomalies and the atmospheric subtropical anticyclone from late boreal summer to early winter. The significance of this potential feedback in reality needs to be further examined with more observational evidence.

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Bohua Huang and J. Shukla

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The monthly mean surface wind stress and winds in the lower troposphere for 1986–92 simulated by the Center for Ocean–Land–Atmosphere Studies atmospheric general circulation model (AGCM) forced with observed sea surface temperature (SST) is compared with observations. It is found that the AGCM surface stress has weak equatorial easterlies during boreal spring and weak El Niño–Southern Oscillation (ENSO) signals over the central and eastern Pacific Ocean. On the other hand, the AGCM winds at 850 mb are found to be in much better agreement with the observations.

An empirical scheme is developed to reconstruct the AGCM surface wind stress, based on the AGCM winds from 850 mb. The reconstructed wind stress is more consistent with observations for both annual and interannual variability. A series of numerical experiments are conducted using the observed, AGCM, and reconstructed surface stress to force an ocean general circulation model. The results demonstrate that the low-frequency ENSO signals are significantly improved in the OGCM when the reconstructed dataset replaces the original AGCM stress. Improvements are evident in more realistic SST anomalies and variability of the thermocline depth.

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