THE REGIME DEPENDENCE OF DEGREE-DAY FORECAST TECHNIQUE, SKILL, AND VALUE

An investigation into the manner in which forecasters adjust their rel iance on particular pieces of forecast information as the large-scale flow pattern evolves into different regimes, and the relationship betw een those adjustments and forecast skill and value is presented. For t he cold season months (December-February) of the period 1 January 1973 through 31 December 1992, a total of three regime types (identified t hrough cluster analysis) comprising 63% of the days were identified. A framework for investigating the weighting of pieces of forecast infor mation, based upon multiple regression techniques, was applied to Nati onal Weather Service (NWS) degree day forecasts (constructed from the 12-24-h minimum and 24-36-h maximum temperature forecasts) for this pe riod. It was determined that substantial changes in the usage of Model Output Statistics (MOS) by NWS forecasters have occurred with the adv ent of the improved numerical model guidance represented by the Limite d Fine Mesh (LFM) MOS, and that these changes occurred in response to improvements in the longer-range forecasts (validating 24-36 h from th e initial time). However, it was also shown that this increased weight ing of MOS was situation dependent and that forecast skill and value w ere maintained under large-scale flow regimes in which MOS was less us eful through significant adjustment of forecast technique. Overall, sk ills were found to be lowest for flows in which either the variability of the MOS weight was highest (reflecting uncertainty in its reliabil ity) or in which limitations of that guidance were evident. These resu lts are then related to earlier investigations concerning the relation ship between forecast skill and experience.