Recent development in high-resolution regional modeling produced realistic representation of Madden-Julian oscillation (MJO) signals. However, large errors remain in the predicted timing and amplitude of MJO phases. To improve our understanding of MJO and tropical weather and make better predictions, we need better observing systems and data assimilation systems in the tropics to provide initial condition for the models. In this study, we conducted an Observing System Simulation Experiment (OSSE) using the PSU WRF ensemble data assimilation system to test the relative impact to analysis accuracy from using satellite-retrieved temperature and moisture profiles, atmospheric motion vectors (AMV) and sounding array from the DYNAMO field campaign. Assimilating satellite temperature and moisture profiles reduces analysis error in the thermodynamic variables, also bringing some positive impact to the horizontal wind field through dynamic adjustment. Adding the AMVs improve the wind analysis at higher model levels. The sounding array provides crucial information for low-level wind. However, due to its poor spatial coverage, the analysis error for low-level wind remains large. Our results serve as a guide to the design of future observing systems over the tropics. We also discuss the potential increase in practical predictability of tropical weather when the aforementioned observations are assimilated.

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*email: yxy159@psu.edu
*Preference: Oral