Lapse Rate Adjustments of Gridded Surface Temperature Normals in an Area of Complex Terrain: Atmospheric Reanalysis versus Statistical Up-Sampling

The applicability of elevation-regression based interpolation methods for long-term temperature normals, for example the Parameter-elevation Regressions on Independent Slopes Model (PRISM), becomes increasingly limited in data sparse, complex terrain such as that found in mountainous British Columbia (BC), Canada. Recent methods to improve both the resolution and accuracy of interpolation models have focused on the development of "up-sampling" algorithms based on local lapse rate adjustments to the original interpolated surfaces. Lapse rates can be derived from statistical models (e.g., elevation-based polynomial regression equations) or dynamical models (e.g., vertical temperature profiles from numerical weather prediction (NWP) models). This study compares a widely used statistical up-sampling algorithm, ClimateBC, with two NWP reanalysis products, the National Centers for Environmental Prediction/National Corporation for Atmospheric Research, Reanalysis 1 (NCEP1) and the more modern European Centre for Medium-range Weather Forecasts (ECMWF) Reanalysis Interim (ERA-Interim). Thirty-year climate normals for maximum and minimum temperatures were calculated using statistical up-sampling and NWP lapse rate adjustments to existing PRISM-based climate normals at a subset of stations in BC. Specifically, up-sampling model evaluation was performed using 1951-80 climate normals from an independent set of 54 surface stations (1 m to 2347 m) which were not included in the PRISM interpolation or assimilated into the NWP reanalysis products. All models performed similarly for minimum temperature, which showed only a slight improvement over PRISM. For maximum temperature, ClimateBC, NCEP1 and ERA-Interim all performed significantly better than PRISM, in particular during spring and summer. The ERA-Interim reanalysis outperformed NCEP1 in almost all months. The results suggest that lapse rate adjustment algorithms based on reanalysis products will have greater potential as progress continues on developing NWP components.