Collaborative Research: Dynamics and Predictability of Tropical Weather and Climate through Cloud-resolving Ensemble Assimilation of Sounding and Radar Observations from DYNAMO

The Madden-Julian Oscillation (MJO), which is the dominant mode of the tropical atmosphere at intraseasonal time scales, has significant impacts on many aspects of weather and climate across the globe. While the basic features of the MJO have been revealed by observations for many years, its underlying dynamics remain poorly understood and current generation numerical weather and climate models have low skills in simulating and predicting MJO events. The recently completed NSF-sponsored Dynamics of the Madden-Julian Oscillation (DYNAMO) field campaign targeted processes critically related to MJO initiation in the Indian Ocean.

This grant seeks to use ensemble-based data assimilation (EnDA) based on the Weather Research and Forecasting (WRF) model to explore the dynamics and predictability of tropical weather and climate from convective to intraseasonal scales by assimilating radar, sounding, and satellite observations collected during DYNAMO. The DYNAMO observations of particular interest to the research are those from three Doppler radars, and those from an enhanced mesoscale sounding network.

Major objectives of the research include: (1) exploring the most reliable and effective EnDA methods for tropical weather analysis and forecasts ranging from convective to regional scales by comparing different variational, ensemble-based and hybrid data assimilation approaches; (2) conducting convective- and regional-scale reanalysis using the most accurate and affordable EnDA method over the entire DYNAMO period, and verify with regular and field observations as well as existing global analysis or reanalysis; and (3) examining the dynamics and predictability of tropical weather and climate (including the MJO) from convective to intraseasonal scales using convection-permitting (i.e., very high temporal and spatial resolution) ensemble analysis and forecasting.

Intellectual merits: The combination of the EnDA technique with field observations constitutes a potentially significant advance in data assimilation, and our understanding of the dynamics, evolution, prediction, and predictability of tropical weather and climate from convective to intraseasonal scales. The analysis and forecasts also provide an efficient pathway to bridge the understandings of tropical weather and climate from convective to intraseasonal scales.

Broader impacts: The research efforts will provide educational benefits through the extensive participation of a doctoral graduate student and a postdoctoral scientist. Research findings will also be directly used in classroom teaching and for directing undergraduate research projects. The findings on the initialization, prediction, and predictability of MJO events will improve operational forecasts of tropical weather and climate, providing a direct benefit to the general public, whether they live in the tropics or in areas around the world that are affected by MJO events. The EnDA systems developed from this support, and the reanalysis of DYNAMO observations by WRF simulations, will be made freely available online with ample documentation to benefit the larger academic community.