The GOES-R era will begin early in the next decade. GOES-R instruments will provide superior spatial and temporal resolution and more spectral bands than the current GOES satellites. This paper will describe the development of GOES-R products at the NESDIS Regional and Mesoscale Meteorology Branch (RAMMB) and Cooperative Institute for Research in the Atmosphere (CIRA).

Numerical simulations and existing in situ and satellite data are being used to better understand the capabilities of the advanced GOES-R instruments for mesoscale weather analysis and prediction. The emphasis of our science study is on mesoscale atmospheric phenomena that evolve on time scales faster than, and at spatial resolution greater than, those normally sampled by current GOES. These phenomena include tropical cyclones, severe weather and mesoscale aspects of winter weather, including lake-effect snowfall, as well as the detection of atmospheric hazards such as fog, dust and volcanic ash. We have produced a large dataset of proxy GOES-R data which consist of synthetic imagery and existing satellite data. Using a sophisticated cloud model and accurate radiative transfer modeling we produced synthetic imagery for several mesoscale events. Fire hotspots were embedded into these mesoscale study cases to support the development and testing of fire algorithms. AVHRR and MODIS data together with current GOES datasets of 11 tropical cyclone cases were collected as proxy GOES-R data for the tropical cyclone intensity algorithm development. A ground-based global lightning dataset and Meteosat data are also being used as a proxy for GOES-R instruments.

The prototype mesoscale product development using these datasets will be described, along with plans for the future. The development of GOES-R training material will also be summarized.