Future instruments aboard GOES-R will resolve atmospheric features beyond today's capabilities in both time and space. Although these data are expected to improve NWP guidance at 48 hours and beyond, a greater benefit from these detailed time/space-frequency data may come from objective nowcasting systems that assist forecasters in identifying rapidly developing, extreme weather events 1-6 hours into the future. These ‘NearCasting' systems must be able to detect and retain extreme variations in the atmosphere, incorporate large volumes of high-resolution asynoptic data. Because of the perishability of these very-short-range forecast products, they may require numerical approaches that are notably different from those used in numerical weather prediction, where the forecast objectives cover longer time periods and can take longer to run.

At previous meetings, a new LaGrangian approach has been shown that optimizes the impact and retention of information provided by satellites, specifically detecting and preserving intense vertical and horizontal variations observed in the various data fields observed over time. To test the system, full resolution (10 km) moisture products from current GOES sounders have been used to update and enhance current operational RUC forecasts. Results show that the LaGrangian system captures and retains details (maxima, minima and extreme gradients) important to the development of vertical moisture gradients (an indicator of convective instability) 3-6 hours in advance, even after IR observations are no longer available due to obscuration by the developing convection itself.

Although these tests provide prototype examples of NearCast products that will be available at higher resolution using GOES-R ABI data, additional experiments are planned to expand the utility of existing and future GOES observations. A key to these NearCasting experiments is the use of parameters whose forecasts are both 1) critical in identify the pre-convective environment and 2) observed well by GOES. Instead of respecting the guidance products to 2 or 3 layers of moisture data, 6 to 8 layers of temperature data will also be projected forward in time and then combined to determine areas where a variety of stability indices are undergoing substantial changes. Candidate indices include the Lifted Index, Totals Index, CAPE, CIN, and Convective Instability among others. Because of the desire to reduce false alarms, both destabilization and stabilization will be studied.

Details of the planned NearCasting enhancements, as well as plans for assessing products within NWS WFOs and NCEP Service Centers, will be included in the discussion.