AMIP II Diagnostic Subproject:

Synoptic to Intraseasonal Variability

Julia M. Slingo1 and Kenneth R. Sperber2
1Department of Meteorology, CGAM, University of Reading, UK
2Program for Climate Model Diagnosis and Intercomparison, LLNL, CA, USA

The Madden-Julian (Intraseasonal) Oscillation (IO) is a dominant mode of variability in the tropics (Madden and Julian 1971, 1972). It has long been recognized that it is manifested on a time scale of ~30-60 days through large-scale circulation anomalies, which occur in conjunction with eastward evolving convective anomalies in the tropical eastern hemisphere. Characteristics of the life cycle of intraseasonal oscillations have been described by many authors (e.g., Knutson and Weickmann 1987, Rui and Wang 1990, Hendon and Salby 1994, Matthews and Hoskins 1996, Sperber et al. 1996). The principal focus of research in Subproject 1 of AMIP I involved the diagnosis and assessment of the IO in 15 participating AGCMs. The results, described in Slingo et al. (1996), indicated that:

    1) No model was able to capture the dominance of the intraseasonal oscillation seen in the ECMWF analyses; the simulated oscillations were usually weaker and not as spatially coherent as observed; the correct seasonality was not well reproduced.

    2) Buoyancy closure of a convection scheme may be preferable to moisture convergence for the simulation of intraseasonal oscillations. Models with the most realistic intraseasonal oscillations appeared to have precipitation distributions which were well correlated with warm sea surface temperatures.

    3) Those models with weak intraseasonal activity tended also to have a weak seasonal cycle; an accurate description of the basic climate may be a prerequisite for producing a realistic intraseasonal oscillation.

Following the basic assessment of 15 AGCMs, Sperber et al. (1996) analyzed case study periods from two of the models that produced the most realistic IO's to investigate the initiation and propagation of the IO and the potential mechanisms involved. The model results were compared with a similar diagnosis of NCEP/NCAR reanalyses. This study indicated that:
    1) The models were unable to simulate the large scale organization of convection associated with the IO and its eastward migration from the Indian Ocean into the western Pacific. Rather, the simulated convection and latent heat flux tended to lock onto the west Pacific warmpool.

    2) Evaporative wind feedback and frictional wave-CISK are not the principal mechanisms for maintaining eastward propagation of the IO in either the NCEP/NCAR reanalyses or in the models.

    3) Sea surface temperatures display intraseasonal variability which may interact coherently with the IO and thus may play a role in its initiation and propagation.

The results from AMIP I show that a realistic simulation of the IO has yet to be achieved. The nature of the IO, particularly its periodicity, its seasonality and its sporadic occurrence, has still to be unraveled. However, Slingo et al. (1996) and Sperber et al. (1996) have demonstrated the considerable benefits and advances in understanding that can be achieved through inter- comparison of models and validation against reanalyses.


As in Subproject 1 of AMIP I, the IO will continue to be a focus of research. However, with improved availability of model history data, more emphasis will be placed on the synoptic timescale and its interaction with the IO. The main emphasis will continue to be on the coherent eastward propagating IO which occurs predominantly during northern winter. The intraseasonal activity during northern summer, which is characterised by northward propagation and is closely linked to Asian summer monsoon active/break periods, will be studied in a related subproject. Specifically, we plan to:

1) Provide a continuing assessment of the skill of participating models to simulate the IO, including its seasonality and interannual variability.

2) Investigate further the processes responsible for the initiation, maintenance, and dissipation of the IO.

3) Assess the reproducibility of the interannual behaviour of the IO and its relationship with ENSO.

4) Investigate the interdependence of the multiple time scale interactions in the tropics (e.g., cloud clusters and super cloud clusters, westerly wind bursts); to explore tropical-extratropical interactions which may affect, or be affected by the IO (e.g., cold surges).

5) Investigate the impact of intraseasonal variability in modulating the seasonal progression and interannual fluctuations of the Austral Monsoon. It is hypothesized that the intensity, frequency and duration of active and break periods associated with the IO may be important modulators of the intensity of the monsoon.

Methodology and Validation

Preliminary identification of IO will be made from analyzing hovmoller diagrams of 200hPa velocity potential. The velocity potential is the field in which the IO is most readily identified. The forced Rossby wave response and the vertical structure of the IO will investigated using eddy streamfunction at 200hPa, 850hPa and the surface. Bandpass filtering, Fourier analysis, space-time decomposition and empirical orthogonal function analysis will be used to identify the characteristics of the IO. Use of wavelet analysis may facilitate diagnosis of the interdependence of the multiple time and space scales of convection.

The life-cycle of the IO will be studied from a statistical point of view via lagged correlation analysis with OLR, precipitation (indicative of diabatic heating), vertical motion at 500hPa, clouds, and surface latent, shortwave, longwave and sensible heat fluxes. Specific case studies will be analyzed in detail to understand the surface energy budget for comparison against TOGA/COARE observations (Zhang 1996, Lau and Sui 1996, and Flatau et al. 1996) and reanalysis. In this way we will be able to investigate the mechanisms by which the models initiate and maintain the eastward propagation of the IO.

Extensive use of the NCEP and ECMWF reanalysis data sets will be made in order to assess the ability of the AMIP-II models to simulate IO variability. The degree of agreement among these reanalysis products will provide a measure of observational uncertainty against which the model performance can be interpreted. We will use the AMIP-I integrations as a baseline against which model improvement can be judged so that we may assess our understanding of the physical processes that may be important for IO simulation.

Data requirements

Extensive use of the 6-hourly data will be made, particularly from those models for which the Table 6 6-hourly supplementary output is available (only with the data from Table 6 can we probe mechanisms of IO variability, for those models that do not supply this optional data, only the basic characteristics of the IO can be identified). From Tables 3 and 6 we require:

    u- and v-wind component at 200hPa, 850hPa and the surface (from which divergence, relative vorticity, streamfunction and velocity potential can be calculated)
    vertical motion at 500hPa
    Outgoing longwave radiation
    surface downwelling longwave radiation
    surface upwelling longwave radiation
    surface incident shortwave
    surface reflected shortwave radiation
    surface sensible heat flux and surface latent heat flux
    total precipitation rate
    precipitable water
    total cloud cover
Evaluation of the basic state of the models is important to establish the context within which the IO variations are embedded. Therefore, monthly mean output for the afore-mentioned variables will be required (Tables 1 and 2). Additionally, upper-air data on the WMO standard levels will be required for the: temperature tendency due to total diabatic heating, temperature tendency due to SW radiation, temperature tendency due to LW radiation, temperature tendency due to moist convective processes, temperature tendency due to dry convective processes, temperature tendency due to large scale precipitation, and total moisture tendency due to diabatic processes.


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