Regional climate modelling in New Zealand: Comparison to gridded and satellite observations
The climate of New Zealand is highly variable, both spatially and temporally, due to a mixture of complex topography and location in the Southern Hemisphere, mid-latitude westerlies. The representation of New Zealand climate in General Circulation Models (GCMs) is too coarse to provide meaningful regional climate statistics. Therefore empirical-statistical or dynamical downscaling methods should be applied to global model data to understand regional climate in terms of the large scale flow. In this study, the focus is on dynamical downscaling where a Regional Climate Model (RCM) is used. The RCM is forced by both reanalysis and GCM data and run for thirty years in each case. Climate statistics from the model for 1980-1999 are compared with gridded observations. The geographical distribution of maximum and minimum surface air temperatures compare well with the gridded observational data (spatial correlation values >0.9) with low temperatures in upland areas and higher temperatures in lowland and northern areas. However, temperature biases are also evident, with maximum surface air temperature being too low and minimum surface air temperatures too high. The model also captures the west – east gradient in precipitation across the mountainous South Island very well (spatial correlation values >0.75). Biases in precipitation are also analysed and tend to be negative (too little precipitation), especially in winter. Biases in the GCM-forced regional model results are similar to, but slightly larger than, those in the reanalysis-forced run, owing to additional circulation errors coming from the global model.