The Madden-Julian Oscillation (MJO) is the dominant mode of tropical convection variability on the intraseasonal time scale. The MJO initiates in the western equatorial Indian Ocean and propagates eastward as a couplet between multi-scale convection and large-scale circulation. Though upscale/downscale modulations and tropical –extratropical teleconnections, the MJO influences the weather activity and climate variability around the globe. The recurrent nature of the MJO influences the weather activity and climate variability around the globe. The recurrent nature of the MJO with a period of 30-60 days offers an opportunity to bridge the gap between weather forecasting and seasonal prediction. However, current state-of-the-art global models are significantly challenged in realistically simulating the MJO, which severely hampers our capability of predicting its global impacts.
Great efforts have been made to improve the prediction skill of the MJO at NOAA NCEP. Dynamical forecasts from the NCEP Climate Forecast System (CFSv1) have been produced in real-time since 2004. A new Climate Forecast System (CFSv2) is being developed and will replace the earlier version (CFSv1). Additionally, a new Climate Forecast System Reanalysis (CFSR) has recently been completed. The CFSR is superior in capturing intraseasonal convective variability as compared to the previous NCEP reanalyses and is used to initialize the CFSv2. Despite these efforts, outstanding problems in the MJO forecast still remain. Preliminary analysis shows that while the CFSv2 has a better overall skill than the CFSv1, it consistently forecasts too slow eastward propagation. The proposed research aims to take advantage of the unprecedented data that will be collected during DYNAMO/AMIE field campaigns and the CFSR to advance our understanding of the MJO initiating and propagation, and to explore the pathway to improve the representation of the MJO in the CFSv2.
To achieve the above objectives, the following steps will be taken:
1) Relevant processes revealed from previous studies on MJO initiation and propagation will be documented with the CFSR, outputs of the CFSv2 and a model at UH.
2) Results from the CFSR, CFSv2, and the UH model will be carefully compared and further validated with DYNAMO/AMIE observations and possible relationships between errors in the MJO forecasts and errors in associated atmospheric (e.g., heating and moistening profiles, low-level convergence, etc.) and oceanic (e.g., SST) fields will be examined to assess the impacts of atmospheric model physics and oceanic surface variability.
3) Numerical experiments with the CFSv2 and UH model will be conducted to assess the impact of atmospheric model physics (e.g., detrainment of shallow convection and trigger of deep convection).
4) Further numerical experiments with atmosphere-only components of the CFSv2 and UH model will be performed to assess the impact of forecast SST errors and to test the use of a high-resolution 1-dimensional mixed-layer ocean model.
This activity is expected to improve the overall prediction skill of the MJO in the NCEP mode. This project directly responds to the priority 3 of FY2011 ESS program “understanding and Improving Prediction of Tropical Convection”. The proposed study will further our understanding of the physical processes governing the initiation and propagation of the dominant tropical convection variability on the intraseasonal time scale: the MJO. The main accomplishment of this project will be to improve the prediction skill of the MJO and the associated weather and climate variability in the CFSv2, contributing to the economic and societal well-being of the Nation.