Stable isotope variations in precipitation: simulations and comparison with observations (Yunnan Plateau, High Asia)

Abstract

Stable isotopes in precipitation, both liquid (rain) and solid (snow), can be suitable tracers for hydrological cycles because their concentrations reflect the cumulative record of physical phase changes. Distribution of stable isotopes in precipitation over High-Asian monsoon regions, including Yunnan Plateau is investigated. It has two noticeable features: firstly, the stable isotopes in precipitation distinctly decrease; and secondly, the stable isotopes in precipitation demonstrate smaller concentrations during rainy seasons and higher values during dry seasons. These features were found by the MUGCM simulation developed in the Melbourne Univertisty. Quantitative effect of the stable isotopes in precipitation takes place at different time scales, i.e. in diurnal, monthly or annual variations. Relative to observations, the simulated δ¹⁸O in precipitation shows stronger dependence on precipitation. In the diurnal course, the simulated regression equations of δ¹⁸O in precipitation versus precipitation amount are in good agreement with the observed values at Tengchong and Simao, except that the simulated δ¹⁸O/P curve slope is slightly smaller than the observed one at Mingzi. In the monthly and annual courses both, the simulated and observed δ¹⁸O/P slopes are smaller than it is in the diurnal course. For individual station, the local meteoric water line (LMWL) is simulated well at Mengzi and Tengchong. However, the simulated result does not reproduce truly the observed relationship between δD and δ¹⁸O in precipitation at Simao and Kunming where the LMWL inclination is larger 8.0, and a shift along the y-axis higher 10.0. In addition, all simulated LMWL slopes are higher the observed ones at four stations, suggesting that the GCM can overestimate the decreasing of Hydrogen Deuterium Oxide and, thus, underestimate the second-order parameter, i.e. the deuterium excess, in a particular region Yunnan.