Quantifying Feedbacks Between Convection and Radiation During the MJO using DYNAMO Observations and Climate Models

Reduced outgoing longwave radiation (OLR) measured by satellites indicates convective activity, so intraseasonal variability of OLR is often used as a key indicator to track zonal propagation of the Madden Julian Oscillation (MJO). A compelling result emerging from the DYNAMO (Dynamics of the Madden-Julian Oscillation) field experiment is that surface radiation is also modulated by the MJO. Strong clear-sky solar radiation on the sea surface during the convectively suppressed phase of the MJO warms the sea surface temperature (SST) by ~1° C. The warmer and moister atmospheric boundary layer primes the atmosphere with convective instability.

We measured SST, surface solar and thermal longwave radiation, and surface turbulent heat fluxes in the central Indian Ocean (80°E, 0°N) over most of 3 MJO periods aboard the ship Revelle the during the DYNAMO field campaign. Soundings from the DYNAMO array measured the atmospheric thermodynamic and moisture structure. Coincident satellite data (e.g. CERES) provide outgoing top-of-atmosphere (TOA) radiative fluxes, permitting the calculation of the net radiative divergence in the atmosphere. 

We propose to use these observations to study the relationship of convection and tropospheric moisture to the TOA and surface radiative fluxes on intraseasonal time scales. Using the sounding thermodynamic profiles we will calculate profiles of radiative flux and flux divergence heating rates with a radiative transfer model.

We will capitalize on the new DYNAMO data set to test how humidity anomalies and clouds modulate the strength and height of atmospheric radiative divergence, and whether the radiative divergence varies in such a way as to amplify intraseasonal convective anomalies associated with the MJO.

Diverse models show various levels of skill at reproducing MJO-like tropical intraseasonal variability. We will assess tropical intraseasonal variability, in particular radiative budgets, in the CMIP5 models. Do models that simulate realistic intraseasonal variability also reproduce observed relationships among atmospheric moisture, radiative divergence, and convection on intraseasonal timescales? In CMIP5 models and the DYNAMO observations, we will quantify how the widespread deep clouds associated with the MJO affect the regional radiative energy balance of at the surface and the top of the atmosphere.

Improved understanding of the radiative processes involved in generating and maintaining the MJO supports prediction of consequential intraseasonal weather variability, and supports NGSP’s 5-year NOAA climate objectives: “1) improved scientific understanding of the changing climate system and its impacts; 2) assessments of current and future states of the climate system that identify potential impacts and inform science, service, and stewardship decisions.