Using CYGNSS to Observe Convectively Driven Near-Surface Winds in Tropical Precipitation Systems during Madden-Julian Oscillation Events

The Cyclone Global Navigation Satellite System (CYGNSS) is a multi-satellite constellation launching in November 2016. The primary objective of CYGNSS is to use bistatic Global Positioning System (GPS) reflectometry to accurately measure near-surface wind speeds within the heavily raining inner core of tropical cyclones. CYGNSS also features rapid revisit times over a given region in the tropics - ranging from several minutes to a few hours, depending on the constellation geometry at that time. Despite the focus on tropical cyclones, the ability of CYGNSS to provide rapid updates of winds, unbiased by the presence of precipitation, has many other potential applications related to general tropical convection. We report on a study that leverages the CYGNSS End-To-End Simulator (E2ES) to investigate the ability of CYGNSS to map convectively driven winds in large precipitation systems associated with the Madden-Julian Oscillation (MJO) onset in the Indian Ocean. The E2ES ingests geospatial vector wind fields, such as from a weather model, and determines how CYGNSS would observe the scene via modeling CYGNSS and GPS satellite orbits, fields of view, and retrieval algorithms.

            For this study we have assimilated observations from the Dynamics of the MJO (DYNAMO) field campaign in 2011-2012 into the Weather Research and Forecasting (WRF) model and produced multiple simulations of MJO-onset convective events. Then, we analyzed how CYGNSS would observe these convective systems with the E2ES. Based on our simulations, CYGNSS should be capable of observing convectively driven wind events, including downdraft-induced outflows as well as Westerly Wind Bursts. In addition, CYGNSS should be capable of providing useful information about the spatiotemporal evolution of these events. These capabilities were confirmed using long-term simulation data from the Goddard Earth Observing System Model, Version 5 (GEOS-5), Nature Run. These results indicate that CYGNSS provides potential advantages relative to existing scatterometers. The relevance of these observations for studying and forecasting the development of MJO-like convective systems is being investigated with WRF data assimilation experiments. In particular, we are investigating how CYGNSS may improve air/sea flux estimates from satellite in the presence of deep convection, and the extent to which that improves model representation of convective evolution.