Evolution of precipitation structure during the November dynamo MJO event: Cloud-resolving model intercomparison and cross validation using radar observations


Evolution of precipitation structures are simulated and compared with radar observations for the November Madden-Julian Oscillation (MJO) event during the DYNAmics of the MJO (DYNAMO) field campaign. Three ground-based, ship-borne, and spaceborne precipitation radars and three cloud-resolving models (CRMs) driven by observed large-scale forcing are used to study precipitation structures at different locations over the central equatorial Indian Ocean. Convective strength is represented by 0-dBZ echo-top heights, and convective organization by contiguous 17-dBZ areas. The multi-radar and multi-model framework allows for more stringent model validations. The emphasis is on testing models' ability to simulate subtle differences observed at different radar sites when the MJO event passed through. The results show that CRMs forced by site-specific large-scale forcing can reproduce not only common features in cloud populations but also subtle variations observed by different radars. The comparisons also revealed common deficiencies in CRM simulations where they underestimate radar echo-top heights for the strongest convection within large, organized precipitation features. Cross validations with multiple radars and models also enable quantitative comparisons in CRM sensitivity studies using different large-scale forcing, microphysical schemes and parameters, resolutions, and domain sizes. In terms of radar echo-top height temporal variations, many model sensitivity tests have better correlations than radar/model comparisons, indicating robustness in model performance on this aspect. It is further shown that well-validated model simulations could be used to constrain uncertainties in observed echo-top heights when the low-resolution surveillance scanning strategy is used.



precipitation, evolution, observations, atmosphere


This study is mainly funded by grant DE-SC0008568 of the U.S. Department of Energy, Regional and Global Climate Modeling Program and Atmospheric System Research Program. X. Li would like to acknowledge additional funding from NASA grant NNX13AQ29G. S. Wang acknowledges support from National Science Foundation under grants AGS-1062206, AGS-1305788, and AGS-1543932. W.-K. Tao is also supported by the NASA Precipitation Measurement Mission (PMM) and NASA Modeling Analysis and Prediction (MAP) program. Both S-PolKa and C-band radar data are archived at DOE ASR's data site https://asr.science.energy.gov/data. TRMM PR data can be obtained through NASA website https://pmm.nasa.gov/data-access/downloads/trmm. The model simulations are archived on DOE server http://portal.nersc.gov/project/cpmmjo and NASA's mesoscale model webserver https://cloud.gsfc.nasa.gov. The RMM index is from www.bom.gov/au/climate/mjo/. Shaocheng Xie and Yunyan Zhang from Lawrence Livermore National Laboratory and Paul Ciesielski from Colorado State University provided large-scale forcing data and many insights in the interpretations. We would also like to thank Samson Hagos at PNNL for his help in archiving data. Zhe Feng at PNNL and Courtney Shumacher at Texas A&M provided valuable suggestion on using surface-based radar data. Acknowledgment is also made to the NASA Center for Climate Simulation, NASA Advance Supercomputing Division, and NASA Precipitation Processing System, for resources used in this research. PMEL contribution 4684 (C. Z.).



Li, X., Janiga, M.A., Wang, S., Tao, W.K., Rowe, A., Xu, W., Liu, C., Matsui, T. and Zhang, C., 2018. Evolution of precipitation structure during the November DYNAMO MJO event: Cloud‐resolving model intercomparison and cross validation using radar observations. Journal of Geophysical Research: Atmospheres, 123(7), pp.3530-3555.