Increasing Difference of China Summer Precipitation Statistics Between Percentage Anomaly and Probability Distribution Methods Due to Tropical Warming

Abstract

Abstract Precipitation anomaly grades are usually defined by the percentage anomaly (Pa) or probability distribution (Pd) methods. However, the difference between the two may lead to different estimates for the same events, creating difficulty in judging the severity of the events. Here, we quantify the difference in measuring precipitation variability in China between Pa and Pd methods and analyze physical meaning and influencing factors of the difference. The results show that Pa tends to underestimate the domain of wetness (e.g., it underestimated 7.67% in June 2018) and overestimate/underestimate the severity of extreme wetness (>1.5σ)/dryness (<–1.3σ) compared to the Pd method. Because precipitation has a positive skewed distribution, and precipitation maximum values have a larger influence on Pa than on Pd. On the other hand, uniform Pa thresholds for classifying drought grades at all stations are unreasonable. Because of an asymmetrical range of actual Pa value, Pa fails to symmetrically reflect the degree of drought and flood. Spatially, the large difference usually appears in the areas with extreme precipitation. Therefore, the more extreme precipitation stations, the greater the spatial dispersion of precipitation and the greater the total difference between Pa and Pd in whole China. We further find that the Pa‐Pd difference is significantly related to a concurrent warming of the tropical Indian Ocean and the tropical Pacific sea surface in spring. And the Pa‐Pd difference is rising at 0.022σ/10a with the increase of extreme events associated with the ocean warming, which deserves attention from the decision‐making departments.

Keywords

• extreme climate
• precipitation anomaly percentage
• probability distribution
• tropical ocean surface warming