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Home » A Quantitative Analysis of Convective Mass Flux Parameterizations Using Direct Observations from the DYNAMO Field Program
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A Quantitative Analysis of Convective Mass Flux Parameterizations Using Direct Observations from the DYNAMO Field Program

The 2011 DYNAMO investigation of the Madden Julian Oscillation (MJO) included an elaborate, multi-platform observation field study with ships, islands, and aircraft in the Indian Ocean. The R/V Revelle was a primary platform for surface-based near-surface, boundary-layer, cloud, and precipitation observations. Observations from platforms (and sets of platforms) must be integrated for the next stage of research. We propose to address this (partly) using observations made on Revelle, with narrow focus on direct analysis of a specific DYNAMO hypothesis for MJO initiation – pre-moistening of the lower free troposphere by shallow convection. The mechanism for this pre-moistening is vertical transport of water (vapor plus liquid) by shallow convective clouds. Mass flux approximations form the core of must cumulus parameterizations (see Lappen and Randall, ‘Toward a Unified Parameterization of the Boundary Layer and Moist Convection’, Parts I, II, and III) but the application to shallow convection has historically been neglected because of the observational difficulty – conventional scanning precipitation radars are not suitable for non-or weakly-precipitating clouds.

We propose a project that can be completed with existing data from DYNAMO -focusing on two unique NOAA ship-based remote sensors: the 94-GHz cloud Doppler radar and the high resolution Doppler lidar – but also drawing on other sources of data (microwave radiometer, ceilometer, surface fluxes, rawinsondes, and the C-band radar). The time series of radar in-cloud turbulence profiles will be combined with time series of lidar clear-air turbulence profiles. This will allow – for the first time – direct observations of updraft/downdraft structure with sufficient time/space resolution to measure profiles of convective velocity distributions with the shallow convective cloud explicitly partitioned in the time series. Creation of combined Doppler turbulence retrievals will have synergies with area average statistics from scanning precipitation radar (S. Rutledge). The C-band data will define a larger-scale convective context for our analysis. Data from the NOAA P-3 aircraft flux runs will give additional information on profiles of cloudy vs ‘environment’ moisture concentration. Characterization of the convective mass flux profiles will then allow us to address directly the role of shallow convection in the transport of moisture from the boundary layer into the lower troposphere.

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