Stochastic Forcings Associated with MJO Initiation during DYNAMO

Numerical forecast models have difficulty simulating and forecasting the MJO, especially in its 'initiation' phase in the Indian Ocean, due in part to model deficiencies such as incorrectly tuned parameterizations or inadequate subgrid parameterizations. Data collected during the DYNAMO field campaign captured frequent episodes in which a 'cold pool' of air was laid down on the ocean surface during convective rain events. The dramatic changes in air temperature and winds led to large changes in sensible and latent heat fluxes. Clearly, such events are sub-grid scale to global forecast models. Stochastic forcing might be employed in global models to incorporate the effects of these subgrid events. Linear Inverse Modeling (LIM) can provide an estimate of the geographical covariance statistics and time series of stochastic forcing. Covarying time series of LIM-derived stochastic forcing during the DYNAMO field campaign (October 2011 - March 2012), obtained from global gridded analyses, will be presented. These will be compared with SST and surface heat flux observed by the R/V Revelle during DYNAMO IOP (October 2011 - January 2012). Particular emphasis will be placed on the evolution of these variables during the initial phases of the MJO.