Current models ingest new data from a variety of sources, including surface observations, buoys, airplanes, and GOES-derived data. The derived data might be more accurate and might be used more extensively going forward - I'm not entirely sure.

IMO (as an amateur) the bigger impact is for convective meteorologists that are continually watching satellite imagery and the work that places like CIMSS are doing in analyzing satellite imagery and detecting patterns indicative of severe weather. These detection algorithms will have a higher degree of confidence and can be triggered several minutes earlier now - possibly providing earlier warning for tornadoes.

CIMSS proving ground: https://cimss.ssec.wisc.edu/goes_r/proving-ground/SPC/SPC.ht...

We have some internal models that will benefit from the new GOES 16 data. Particularly the cloud mask product and the higher spatial/temporal resolution will be interesting. We develop our own internal cloudmasks using a custom tool and I'm interested to see how they differ. In anticipation of the higher spatial/temporal resolution data, we're updating our tools to reduce the memory footprint.

GOES-16 will provide the data to allow a significant improvement in forecasts, especially of extreme weather events. Because it can have a variable scan pattern, it can do wide area scans and higher frequency scans tracking storms. The new lightning sensor allows better measurement of storm intensity. It also has finer discrimination for spectral information, 4x increase in resolution, etc.