Altitude Correction of GCM-Simulated Precipitation Isotopes in a Valley Topography of the Chinese Loess Plateau

Altitude is one of the important factors influencing the spatial distribution of precipitation, especially in a complex topography, and simulations of isotope-enabled climate models can be improved by altitude correlation. Here we compiled isotope observations at 12 sites in Lanzhou, and examined the relationship between isotope error and altitude in this valley in the Chinese Loess Plateau using isoGSM2 isotope simulations. Before altitude correction, the performance using the nearest four grid boxes to the target site is better than that using the nearest box; the root mean square error in & delta;18O using the nearest four grid boxes averagely decreases by 0.37 & PTSTHOUSND; compared to that using the nearest grid boxes, and correlation coefficient increases by 0.05. The influences of altitude on precipitation isotope errors were examined, and the linear relationship between altitude error and isotope simulations was calculated. The strongest altitude isotopic gradient between & delta;18O mean bias error and altitude error is in summer, and the weakest is in winter. The regression relationships were used to correct the simulated isotope composition. After altitude correction, the root mean square error decreases by 1.21 & PTSTHOUSND; or 0.86 & PTSTHOUSND; using the nearest one or four grid boxes, respectively, and the correlation coefficient increases by 0.13 or 0.08, respectively. The differences between methods using the nearest one or four grids are also weakened, and the differences are 0.02 & PTSTHOUSND; for root mean square error and -0.01 for the correlation coefficient. The altitude correction of precipitation isotopes should be considered to downscale the simulations of climate models, especially in complex topography.

Automated summary

Altitude is an important factor affecting precipitation distribution, especially in complex topography, and isotope-enabled climate models can be improved by considering altitude correlation. This study examined the relationship between isotope error and altitude in the Chinese Loess Plateau using isotope simulations. Altitude correction significantly reduced root mean square error and increased correlation coefficient in simulated isotope composition, indicating the importance of considering altitude in downscaled climate model simulations.