Spatiotemporal characteristics of different-grade extreme precipitation evolution detected by innovative trend analysis

Understanding the changing characteristics of extreme precipitation (EP) events is essential for formulating effective adaptive measures for water resource and flood hazard management. Although much research focused on annual extreme precipitation variations, there has been little comparison of changing characteristics of extreme precipitation in different grades and seasons. To this end, this study investigated extreme precipitation variations from multiple perspectives in Tai Lake Plain (TLP) during 1966–2015 at spatial (36 stations) and temporal (4 seasons) scales, using an innovative trend analysis (ITA) method with a significant test. Meanwhile, the trends were evaluated separately for low (< 30th), medium (30th–70th), and high (> 70th) grades of extreme precipitation. The ITA method was compared with two traditional trend analysis methods of linear regression (LR) analysis and Mann-Kendall (MK) test. The results indicate that (1) ITA detected a significant upward trend in annual EP indices (except consecutive dry days (CDD)) at the 99% confidence level and similar significant upward trends in summer and winter EPs, while downward trends in spring and autumn in most stations; (2) a relatively stronger intensifying trend of EPs occurred in the southeast and northeast of TLP in summer and winter; (3) from low to high grade, the annual and summer upward trends have continuously strengthened, whereas the downward trends in spring or autumn became weaker to an extent; and (4) significant trends (in three to eight EP indices) that cannot be observed by LR and MK can be effectively identified using ITA. So ITA showed advantages of revealing the hidden trends in climatic time series. These results by ITA can provide an informed reference for flood (or drought) risk management in different seasons and areas across the TLP region.