The release of atmospheric latent heat (LH), resulting from condensation in deep convection, plays an important role driving the global atmospheric circulation, including the Southeast Asian monsoon. In particular, a knowledge of the spatio-temporal structure of the latent heating during the monsoon wet season could be an aid in understanding the interaction between the seasonal cycle of the monsoon and the summer manifestation of the intraseasonal oscillation in the Indian Ocean basin and hence the distribution of precipitation during the wet season.

Several TRMM satellite datasets are available for the entire tropics which have the potential of providing information of LH. Here we use information from the TRMM-CSH dataset to produce and examine three-dimensional LH structures over the Indian monsoon region for the period of 1998-2007. The main CSH algorithm retrieval uses pre-stored profiles for different rainfall systems, type and surface precipitation. A particular goal is to explore the differences in the distribution of the LH throughout the intraseasonal cycle which is considered to be the most important modulator of the summer rainfall climatology of the entire region. TRMM-CSH composites of LH show a clear signal of the 25-80 days especially over the Bay of Bengal and the equatorial Indian Ocean. In addition, time-height LH evolution composites show regular cyclic behavior between maximum and minimum precipitation characteristic of intraseasonal variability.

To explore the validity of the retrievals of LH from the CSH dataset, observations obtained during the South China Sea Monsoon (SCSMEX) are used. The two months of heating budget estimations based on the NESA-IOP observations are compared with CSH LH averages for the same period and geographical region. High correspondence in times of occurrence of positive LH values is found. Interestingly, the negative values of LH are not captured by the CSH dataset. This is due to the method of calculation of the LH by the CSH algorithm, based only in surface precipitation. If there is not precipitation, the algorithm does not provide any heating or cooling. The results show that although the CSH retrievals are capable of representing temporal and spatial characteristics of the Asian monsoonal heating, they have some particular deficiencies with the generation of heating or cooling in non-precipitative regions.