Satellite estimation of precipitation and satellite-derived statistics of mesoscale convective systems (MCS) are analyzed conjunctively to quantify the contribution of the various types of MCS to the water budget of the tropics. This study focuses on two main mesoscale characteristics of the systems: duration and propagation. Overall, the systems lasting more than 12 h are shown to account for around 75% of the tropical rainfall, and 60% of the rainfall is due to systems traveling more than 250 km, a typical GCM grid. A number of regional features are also revealed by factoring in the convective systems’ morphological parameters in the water budget computation. These findings support the challenging effort to account for such mesoscale features when considering the theory on the future evolution of the water budget as well as the physical parameterizations of climate models. Finally, this analysis provides a simple metric for evaluating high-resolution numerical simulations of the tropical water budget. Furthermore, results are shown to be robust to the selection of the satellite rainfall products.

This study focuses on improving the retrieval of rain from measured microwave brightness temperatures and the capability of the retrieved field to represent the mesoscale structure of a small intense hurricane. For this study, a database is constructed from collocated Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and the TRMM Microwave Imager (TMI) data resulting in about 50 000 brightness temperature vectors associated with their corresponding rain-rate profiles. The database is then divided in two: a retrieval database of about 35 000 rain profiles and a test database of about 25 000 rain profiles. Although in principle this approach is used to build a database over both land and ocean, the results presented here are only given for ocean surfaces, for which the conditions for the retrieval are optimal. An algorithm is built using the retrieval database. This algorithm is then used on the test database, and results show that the error can be constrained to reasonable levels for most of the observed rain ranges. The relative error is nonetheless sensitive to the rain rate, with maximum errors at the low and high ends of the rain intensities (+60% and −30%, respectively) and a minimum error between 1 and 7 mm h−1. The retrieval method is optimized to exhibit a low total bias for climatological purposes and thus shows a high standard deviation on point-to-point comparisons. The algorithm is applied to the case of Hurricane Bret (1999). The retrieved rain field is analyzed in terms of structure and intensity and is then compared with the TRMM PR original rain field. The results show that the mesoscale structures are indeed well reproduced even if the retrieved rain misses the highest peaks of precipitation. Nevertheless, the mesoscale asymmetries are well reproduced and the maximum rain is found in the correct quadrant. Once again, the total bias is low, which allows for future calculation of the heat sources/sinks associated with precipitation production and evaporation.

One of the most challenging problems in predicting the Madden–Julian oscillation (MJO) is the initiation of large-scale convective activity associated with the MJO over the tropical Indian Ocean. The lack of observations is a major obstacle. The Dynamics of the MJO (DYNAMO) field campaign collected unprecedented observations from air-, land-, and ship-based platforms from October 2011 to February 2012. Here we provide an overview of the aircraft observations in DYNAMO, which captured an MJO initiation event from November to December 2011. The National Oceanic and Atmospheric Administration (NOAA) WP-3D aircraft was stationed at Diego Garcia and the French Falcon 20 aircraft on Gan Island in the Maldives. Observations from the two aircraft provide a unique dataset of three-dimensional structure of convective cloud systems and their environment from the flight level, airborne Doppler radar, microphysics probes, ocean surface imaging, global positioning system (GPS) dropsonde, and airborne expendable bathythermograph (AXBT) data. The aircraft observations revealed interactions among dry air, the intertropical convergence zone (ITCZ), convective cloud systems, and air–sea interaction induced by convective cold pools, which may play important roles in the multiscale processes of MJO initiation. This overview focuses on some key aspects of the aircraft observations that contribute directly to better understanding of the interactions among convective cloud systems, environmental moisture, and the upper ocean during the MJO initiation over the tropical Indian Ocean. Special emphasis is on the distinct characteristics of convective cloud systems, environmental moisture and winds, air–sea fluxes, and convective cold pools during the convectively suppressed, transition/onset, and active phases of the MJO.