Monthly Archives: April 2018

Paper on DYNAMO CRM Intercomparison and validation published in JGR Atmos

Our paper “Evolution of Precipitation Structure During the November DYNAMO MJO Event: Cloud-Resolving Model Intercomparison and Cross Validation Using Radar Observations” has been published in the Journal of Geophysical Research Atmospheres. I contributed to the radar analysis and provided feedback on the comparisons with the model simulations.

Citation: Li, X., Janiga, M. A., Wang, S., Tao, W.‐K., Rowe, A., Xu, W., et al. (2018). Evolution of precipitation structure during the November DYNAMO MJO event: Cloud‐resolving model intercomparison and cross validation using radar observationsJournal of Geophysical Research: Atmospheres123, 3530-3555. https://doi.org/10.1002/2017JD027775

Abstract

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.