In order to improve daily to seasonal forecasts, numerical weather prediction models require better representation of the interactions among the upper ocean, the marine atmospheric boundary layer (MABL), and tropospheric convection. Tropical weather and midlatitude teleconnections are driven by latent heat released by precipitating clouds. While individual convective clouds are essentially unpredictable, the eastward-propagating convective envelope of the Madden Julian Oscillation (MJO) is predictable on intraseasonal time scales. The MJO dominates variability of zonal wind and outgoing longwave radiation in the tropics, especially over the Indian Ocean. Though the MJO offers the potential for improved predictability, few numerical weather prediction models presently simulate the eastward propagation of the MJO; even fewer simulate MJO development in the central Indian Ocean. The predictability gap in the developing stage of the MJO coincides with a dearth of observations and a corresponding lack of understanding of air-sea interaction and dynamical and convective processes in the Indian Ocean. The Dynamics of the MJO (DYNAMO) program combines observations and modeling to address these problems.
We propose to make a suite of observations from a ship in the Indian Ocean during DYNAMO, to measure surface air-sea fluxes, MABL turbulent mixing, and cloud and precipitation development. Our strategy seamlessly measures processes, from the surface to the MABL and the free troposphere, contributing to tropical convection constituting the MJO. We will equip a US research vessel with radiative sensors and turbulent flux sensors that observe covariances of near-surface temperature, humidity, and velocity; and measure below-cloud mixing and turbulent velocities in the MABL with a scanning Doppler lidar. We also propose to install a cloud observing system consisting of a lidar ceilometer, a multi-channel microwave radiometer measuring integrated liquid and vapor, and a W-band (3.17 mm) Doppler cloud radar, which provides a sensitive vertical profile of cloud liquid water drops, in-cloud turbulence, and precipitation over the life cycle of the cloud.
Our direct observations of surface evaporation, vertical mixing, and cloud formation will complement mesoscale precipitation structure from a scanning C-band (5.3 cm) radar; and largescale tropospheric heat and moisture budgets from rawinsondes released frequently from an array of stations (proposed separately). Flux, turbulence, and cloud data we collect from DYNAMO will be used for testing gridded flux analyses, MABL mixing and cumulus parameterizations, and air-sea interactions in models.