A set of methods to evaluate the below-cloud evaporation effect on local precipitation isotopic composition: a case study for Xi'an, China

When hydrometeors fall from an in-cloud saturated environment toward the ground, especially in arid and semiarid regions, below-cloud processes may heavily alter the isotopic composition of precipitation through equilibrium and non-equilibrium fractionations. If these below-cloud processes are not correctly identified, they can lead to misinterpretation of the precipitation isotopic signal. To correctly understand the environmental information recorded in the precipitation isotopes, qualitatively analyzing the below-cloud processes and quantitatively calculating the below-cloud evaporation effect are two important steps. Here, based on 2 years of synchronous observations of precipitation and water vapor isotopes in Xi'an, China, we compiled a set of effective methods to systematically evaluate the below-cloud evaporation effect on local precipitation isotopic composition. The ΔdΔδ diagram is a tool to effectively diagnose below-cloud processes, such as equilibration or evaporation, because the isotopic differences (δ2H; d-excess) between the precipitation-equilibrated vapor and the observed vapor show different pathways. By using the ΔdΔδ diagram, our data show that evaporation is the major below-cloud process in Xi'an, while snowfall samples retain the initial cloud signal because they are less impacted by the isotopic exchange between vapor and solid phases. Then, we chose two methods to quantitatively characterize the influence of below-cloud evaporation on local precipitation isotopic composition. One is based on the raindrop's mass change during its falling (hereafter referred to as method 1), and the other is dependent on the variations in precipitation isotopic composition from the cloud base to the ground (hereafter referred to as method 2). By comparison, we found that there are no significant differences between the two methods in evaluating the evaporation effect on δ2Hp, except for snowfall events. The slope of the evaporation in proportion to the variation in δ2H (Fi/Δδ2H) is slightly larger in method 1 (1.0 ‰ %−1) than in method 2 (0.9 ‰ %−1). Additionally, both methods indicate that the evaporation effect is weak in autumn and heavy in spring. Through a sensitivity test, we found that in two methods, relative humidity is the most sensitive parameter, while the temperature shows different effects on the two methods. Therefore, we concluded that both methods are suited to the investigation of the below-cloud evaporation effect, while in method 2, other below-cloud processes, such as supersaturation, can still be included. By applying method 2, the diagnosis of below-cloud processes and the understanding of their effects on the precipitation isotopic composition will be improved.