Atmospheric motion vectors (AMVs), derived from the current GOES series of satellites, provide invaluable tropospheric wind information to the meteorological community. AMVs obtained from tracking features (i.e., clouds and moisture gradients) are used for: i) Improving numerical weather prediction (NWP) analyses and forecasts; ii) Supporting short term forecasting activities at National Weather Service (NWS) field offices; and iii) Generating tropical and mesoscale wind analyses.

The GOES-R Algorithm Working Group (AWG) Winds team is working on development of algorithms and software for the generation of Atmospheric Motion Vectors (AMVs) from the GOES-R Advanced Baseline Imager (ABI) to be flown on the next generation of GOES satellites. The GOES-R series of satellites offers exciting new capabilities that are expected to directly benefit and improve the derivation and quality of the AMVs. These new capabilities include: continuous scanning with no loss of imagery due to eclipse or conflicting scanning schedules, higher resolution (spatial and temporal) imagery, and improved navigation. Improved cloud-top height assignments derived from the GOES-R ABI are expected to contribute to further improvement and utilization of the AMV products.

GOES-R AMV software development and testing is being done within the Geostationary Cloud Algorithm Testbed (GEOCAT) framework. This framework supports a tiered algorithm processing approach that allows the output of lower-level algorithms to be available to subsequent higher-order algorithms while supplying needed data inputs to all algorithms through established data structures. MSG/SEVERI imagery is serving as a primary GOES-R ABI proxy data source for the development, testing, and validation of the AMV algorithms. This poster will highlight the AMV algorithms and results from recent testing.