Comparisons of statistical downscaling methods for air temperature over the Qilian Mountains

Air temperature is an important indicator of climate change, as well for understanding changes in hydrology, ecology, and other natural systems. However, meteorological stations that provide reliable observations are usually sparse areas complex terrain, thus limiting our ability to quantify high spatial resolution variability these regions. Here, we apply three statistical downscaling methods daily air output from the sixth Coupled Model Intercomparison Project (CMIP6), validated with 22 over Qilian Mountains. Based on different methods, find RMSE MAE reduced much 59–66%, ratio annual average decreasing 147.9 61.0% 143.3 64.7%, respectively, depending method. Compared original data, based best differed by −2.85±3.61°C during historical 1850–2014 period and, 2015–2100 projections, 2.13±3.30°C SSP1-2.6, −2.13±3.29°C SSP2-4.5, −2.11±3.24°C SSP3-7.0, −2.12±3.23°C SSP5-8.5. The downscaled temperatures show a warming trend ranging 0.15–0.22°C/10 years experiment, 0.08–0.14°C/10 0.24–0.35°C/10 0.43–0.63°C/10 0.52–0.76°C/10 SSP5-8.5 These results indicate accuracy improved compared data. also that, projections have been overestimated.