Potential for Increased Assimilation of Snpp Data Via Direct Readout to Hourly-Updated Global/Regional Numerical Weather Prediction Models for Situational Awareness

Monday, 15 December 2014: 8:15 AM
Stan Benjamin, Haidao Lin, Stephen Weygandt, Ming Hu and Curtis Alexander, NOAA Earth System Research Laboratory, Boulder, CO, United States
Smaller data latency through direct readout will be crucial for hourly updated regional operational models run currently (e.g., NOAA Rapid Refresh (RAP) and 3-km HRRR) and also for future global hourly updated models. Most polar orbiter radiance data are not currently meeting data cut-off availability requirements (~30 minutes) for the current NOAA RAP model. Modest improvement in overall RAP forecast skill is available with full polar-orbiter data availability if data latency was smaller (Lin et al. 2015 a,b) To some extent, this is addressed through “partial cycling” catch-up cycles in RAP, but partial cycling requires parallel NWP cycles and use of more computer resources. Better satellite data coverage (enhanced with reduced data latency) improves forecast skill not only through direct use of more data over more geographic areas but also through improved bias correction leading to more effective use of observations and less data rejection. Increased use of hourly updated models (RAP and HRRR) is clearly occurring for improved decision making. RARS (Regional ATOVS Retransmission Services) is a precursor to full direct readout availability. Initial development toward a global rapid refresh capability now underway and smaller satellite data latency will be critical for successful demonstration of 3h and 1h global updating.