Convective Initiation and 0-6 hr Storm Nowcasting for GOES-R
(1) Information and techniques learned from the creation of an improved proxy AWG CI algorithm can be transferred into improved strategies for direct assimilation of current and future satellite datasets (that describe the CI process), leading to increased accuracy in NWP of the onset of new convective storms.
(2) The assimilation of the raw satellite-based observation fields into rapid-update NWP models such as the Rapid Refresh (RAP) and High Resolution Rapid Refresh (HRRR) will provide the models with a better description of initiating convective storms, leading to beneficial improvements to short- (0-6 hrs) and subsequently longer-range mesoscale forecasts (6-18 hrs).
The HRRR will operate at 3 km resolution and is scheduled to become a National Center for Environmental Prediction (NCEP) operational model in 2014, and hence this activity represents a natural research–to–operational (R2O) transition for GOES-R products into NWP. The overarching theme is improving the short-term mesoscale forecasts, where the assimilation of GOES-R data into the HRRR will provide better timing and locations of future CI, along with the coincident development of an improved proxy AWG CI algorithm toward increasing detection of early-onset storm initiation in advance of radar echoes by up to 45-60 minutes or more.
Shown during this presentation will be recent results of assimilating the GOES-R CI-based latent heating profiles into the RAP mode, that then go on to form new convective storms. Also, analysis involving the use of ~15 NWP fields together with satellite datasets, in a logistic regression model, that produces probabilistic CI nowcasts will be shown (along with feedback from the Hazardous Weather Testbed). Furthermore, analysis will be presented on how satellite-derived cloud property fields improve the GOES-R CI algorithm's performance.