Improvements in Satellite-Derived Short-Term Insolation Forecasting: Statistical Comparisons, Challenges for Advection-Based Forecasts, and New Techniques

Thursday, 18 December 2014: 11:35 AM
Matthew A Rogers, Colorado State University, Fort Collins, CO, United States, Steven D Miller, Colorado State Univ-CIRA, Fort Collins, CO, United States, John M Haynes, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, United States, Andrew K Heidinger, NOAA/NESDIS, Madison, WI, United States, Sue Ellen Haupt, National Center for Atmospheric Research, Boulder, CO, United States and Manajit Sengupta, National Renewable Energy Laboratory Golden, Golden, CO, United States
Using satellite observations from GOES-E and GOES-W platforms in concert with GFS-derived cloud-level winds and a standalone radiative transfer model, an advection-derived forecast for surface GHI over the continental United States is described. In particular, comparisons from the satellite-derived forecast are shown against several SURFRAD sites, with particular attention to developing meaningful error metrics to better demonstrate forecast skill and identify sources of error. Challenges in advection-based forecast techniques, such as forecasting near regions of non-wind-driven cloud systems such as coastal marine stratocumulus, are described, as are methods integrated into the forecast algorithm to identify and address these challenges. Improvements in the particular algorithm with respect to comparison against surface observations, integration of the forecast technique into blended forecast products such as those described by the 'Public-Private-Academic Partnership to Advance Solar Power Forecasting' project spearheaded by the National Center for Atmospheric Research, and other observations germane to satellite-derived solar forecasting are covered using nearly two years of operational forecasts as background.