Parametric gridded weather generator for use in present and future climates: focus on spatial temperature characteristics

摘要

This study presents results of the pilot experiments made with new parametric multi-site multi-variable stochastic daily weather generator (WG) SPAGETTA. The experiments are performed for eight European regions and we focus on spatial characteristics of temperature. The WG is calibrated using the gridded weather data E-OBS. In evaluating the generator, the spatial and temporal temperature autocorrelations derived from the synthetic series were found to perfectly fit the values derived from the calibration data. Next, the WG is validated in terms of the frequency of "spatial hot days" and the annual maximum length of "spatial hot spells". The results indicate a very good correspondence between characteristics derived from synthetic and calibration data. As part of the validation tests, the performance of the WG is compared with a regional climate model (RCM), which shows a similar performance as the generator. In a final experiment, the use of the WG for the future climate is demonstrated, the WG parameters (including the temperature autocorrelations) calibrated with the observed data are modified according to the RCM-based changes in these parameters. While analyzing synthetic series produced with the modified generator, we discuss partial impacts due to changes in individual WG parameters on the spatial hot days and spells. We show that the impacts are mainly (but not only) due to changes in temperature averages. The projected changes in temperature autocorrelations have also some impacts, larger for the spatial hot spells than for the spatial hot days. Climate change impacts on spatial hot days/spells based on the WG are compared with impacts based on the RCM, and we conclude that the differences are mainly due to simplifying assumptions adopted in our pilot experiment.