ProxyVis Multi-Satellite Composite Imagery – An Example of Generating High-Resolution Near Real-Time Composite Imagery with Python

The ProxyVis satellite imagery product uses IR data to generate visible–like imagery at nighttime. ProxyVis enhances forecasters’ ability to see oceanic low-level clouds and can be seamlessly combined with normalized daytime visible imagery to generate full-disk geostationary GeoProxyVis imagery. ProxyVis is used at the NWS (including National Hurricane Center (NHC)) and Joint Typhoon Warning Center (JTWC) operations, and is available for GOES-16/18, Himawari-8/9, and Meteosat-9/10/11 satellites.

For global-scale applications, a single global image might be preferred. To provide that capability, we developed ProxyVis multi-satellite composite product that combines ProxyVis data from all five satellites to provide global coverage in a single image. The multi-satellite composite product is generated in Python using Dask and SatPy. This allows us to generate high-resolution composite imagery in near real-time. Currently, generating a global 5-satellite 0.5 km resolution composite takes approximately 20 minutes on a high-end Linux workstation, only twice as long as it takes to generate full resolution GeoProxyVis imagery from full disk GOES-16 data. Examples of five-satellite GeoProxyVis composite imagery are available online at https://rammb2.cira.colostate.edu/research/goes-r-research/proxyvis/.

The composite imagery has several advantages over imagery from separate satellites. Specifically, it resamples data from all satellites to the same resolution, allows for smooth transition between satellites, and also allows us to control how the data from multiple satellites are combined together. In addition, the composite imagery indirectly corrects for parallax and limb effects in the regions between two geostationary satellites. The presentation will provide details on the multi-satellite composite processing and discuss implications for how the data are viewed in the regions between two geostationary satellites. Further, we will discuss possible use of the high-resolution global composite imagery in operational settings.

Disclaimer: The scientific results and conclusions, as well as any views or opinions expressed herein, are those of the author(s) and do not necessarily reflect those of NOAA or the Department of Commerce.