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Notes: Summary In this paper we have studied the low frequency variability of the sensible and latent heat flux over the Indian monsoon area. We have used an atmospheric energy budget (vertical integrated heat sources and moisture sinks), as well as the similarity theory in order to compute the surface fluxes on a darly basis. Mainly, the three following data sets were used: the First GARP Global Experiment analyzed data, the TIROS-N outgoing longwave radiation data and the Monsoon Experiment precipitation data. Our three main findings are the following. First, the variability of the temperature and the specific humidity at the surface is more important over the land than over the sea on the intraseasonal time scale (30% over land, but 20% over sea). For the wind an energy peak appears clearly around 30–40 days. The surface fluxes show an uneven variance percentage field (10% to 40%); the energy peaks stretch from 10 to 40 days. Second, the wind has a significant influence on the surface fluxes, except at some locations exclusively over the land areas. Of the temperature and the specific humidity, the temperature is the one which influences the fluxes the most. (This influence may be very strong over land.) The specific humidity may have a significant influence, over the land and sea, at the same time. Thus, one cannot neglect the influence of temperature and specific humidity over land on the intraseasonal time scale. Third, we have found a close relation between the propagation of low frequency waves and the propagation of surface flux patterns. This may suggest a feedback mechanism which relates surface processes to the northward propagation of these waves over India.

Notes: Abstract. The ability of 15 atmospheric general circulation models (AGCM) to simulate the tropical intraseasonal oscillation has been studied as part of the Atmospheric Model Intercomparison Project (AMIP). Time series of the daily upper tropospheric velocity poential and zonal wind, averaged over the equatorial belt, were provided from each AGCM simulation. These data were analyzed using a variety of techniques such as time filtering and space-time spectral analysis to identify eastward and westward moving waves. The results have been compared with an identical assessment of the European Centre for Medium-range Weather Forecasts (ECMWF) analyses for the period 1982–1991. The models display a wide range of skill in simulating the intraseasonal oscillation. Most models show evidence of an eastward propagating anomaly in the velocity potential field, although in some models there is a greater tendency for a standing oscillation, and in one or two the field is rather chaotic with no preferred direction of propagation. Where a model has a clear eastward propagating signal, typical periodicities seem quite reasonable although there is a tendency for the models to simulate shorter periods than in the ECMWF analyses, where it is near 50 days. The results of the space-time spectral analysis have shown that no model has captured the dominance of the intraseasonal oscillation found in the analyses. Several models have peaks at intraseasonal time scales, but nearly all have relatively more power at higher frequencies (〈30 days) than the analyses. Most models underestimate the strength of the intraseasonal variability. The observed intraseasonal oscillation shows a marked seasonality in its occurrence with greatest activity during northern winter and spring. Most models failed to capture this seasonality. The interannual variability in the activity of the intraseasonal oscillation has also been assessed, although the AMIP decade is too short to provide any conclusive results. There is a suggestion that the observed oscillation was suppressed during the strong El Niño of 1982/83, and this relationship has also been reproduced by some models. The relationship between a model's intraseasonal activity, its seasonal cycle and characteristics of its basic climate has been examined. It is clear that those models with weak intraseasonal activity tend also to have a weak seasonal cycle. It is becoming increasingly evident that an accurate description of the basic climate may be a prerequisite for producing a realistic intraseasonal oscillation. In particular, models with the most realistic intraseasonal oscillations appear to have precipitation distributions which are better correlated with warm sea surface temperatures. These models predominantly employ convective parameterizations which are closed on buoyancy rather than moisture convergence.

Notes: Abstract The ability of 15 atmospheric general circulation models (AGCM) to simulate the tropical intraseasonal oscillation has been studied as part of the Atmospheric Model Intercomparison Project (AMIP). Time series of the daily upper tropospheric velocity poential and zonal wind, averaged over the equatorial belt, were provided from each AGCM simulation. These data were analyzed using a variety of techniques such as time filtering and space-time spectral analysis to identify eastward and westward moving waves. The results have been compared with an identical assessment of the European Centre for Medium-range Weather Forecasts (ECMWF) analyses for the period 1982–1991. The models display a wide range of skill in simulating the intraseasonal oscillation. Most models show evidence of an eastward propagating anomaly in the velocity potential field, although in some models there is a greater tendency for a standing oscillation, and in one or two the field is rather chaotic with no preferred direction of propagation. Where a model has a clear eastward propagating signal, typical periodicities seem quite reasonable although there is a tendency for the models to simulate shorter periods than in the ECMWF analyses, where it is near 50 days. The results of the space-time spectral analysis have shown that no model has captured the dominance of the intraseasonal oscillation found in the analyses. Several models have peaks at intraseasonal time scales, but nearly all have relatively more power at higher frequencies (〈 30 days) than the analyses. Most models underestimate the strength of the intraseasonal variability. The observed intraseasonal oscillation shows a marked seasonality in its occurrence with greatest activity during northern winter and spring. Most models failed to capture this seasonality. The interannual variability in the activity of the intraseasonal oscillation has also been assessed, although the AMIP decade is too short to provide any conclusive results. There is a suggestion that the observed oscillation was suppressed during the strong El Niño of 1982/83, and this relationship has also been reproduced by some models. The relationship between a model's intraseasonal activity, its seasonal cycle and characteristics of its basic climate has been examined. It is clear that those models with weak intraseasonal activity tend also to have a weak seasonal cycle. It is becoming increasingly evident that an accurate description of the basic climate may be a prerequisite for producing a realistic intraseasonal oscillation. In particular, models with the most realistic intraseasonal oscillations appear to have precipitation distributions which are better correlated with warm sea surface temperatures. These models predominantly employ convective parameterizations which are closed on buoyancy rather than moisture convergence.