PBL AMV and Height Measurements from MISR-GOES and MODIS-GOES Stereo Techniques

A new algorithm (3D-Wind) has been developed to retrieve atmospheric motion vector (AMV) and height simultaneously from rapid refresh images of Geostationary Operational Environmental Satellite (GOES) and snapshot images of low Earth orbit (LEO) sensors (e.g., MISR and MODIS). The method requires no synchronization between GEO and LEO image acquisitions, and relies on stereoscopic views from the two sensors to derive geometric height and rapid refresh GEO images to derive AMVs. The joint retrievals with the 3D-Wind algorithm overcome the limitations and large certainties associated with these measurements as retrieved from a single platform. As demonstrated in the MISR-GOES and MODIS-GOES pairing, the LEO-GEO stereo technique is able to achieve 0.5 m/s and ~300 m accuracy for AMV and height retrievals with a horizontal resolution as high as 2 km. The 3D-Wind algorithm is applied to several dynamical events in the planetary boundary layer (PBL), such as cold air outbreak (CAO) and wildfire. In a CAO event on Jan.31, 2019, the MODIS-GOES stereo retrievals reveal the classical structure of rising PBL height over the open water as the cold air blew across Lake Michigan. The PBL top increased steadily from ~400 m to ~1200 m in ~100 km distance in a background wind of ~8 m/s. On Nov.9, 2019, the MODIS-GOES images captured a moment of rapid development of Camp Fire, one of the deadliest wildfires in California history. The plume reached almost 4 km above the surface as the fire entered the town of Paradise. Also evident is the decreasing plume height as a function of distance from the sources. On Nov.10 some dense fire plumes hovered at ~ 1 km above San Francisco Airport, causing poor air quality and severely reduced visibility. In clear-sky regions, the 3D-Wind retrieval is able to track terrain height closely within < 300 m. These preliminary results deliver a very promising technique and new data product that can be used for studying PBL dynamics and structures. With advanced technologies, LEO imaging sensors can be built as compact as a CubeSat, which allows a cost-effective LEO-GEO and LEO-LEO constellation for future stereo imaging.