An assessment of statistical interpolation methods suited for gridded rainfall datasets. (5th October 2021)

• Record Type: Journal Article
• Authors: Liu, Yuexiao; Zhuo, Lu; Pregnolato, Maria; Han, Dawei
• Is Part Of: International journal of climatology. Volume 42:Number 5(2022)
• Page Start: 2754
• Page End: 2772
• Publication Date: 2021-10-05
• Subjects: ERA5 -- gridded rainfall data -- interpolation methods -- inverse distance weighting -- ordinary Co‐Kriging -- ordinary kriging -- Thiessen polygons -- thin plate spline; Climatology -- Periodicals; Climat -- Périodiques; Climatologie -- Périodiques; 551.605
• DOI: 10.1002/joc.7389
• Languages: English
• ISSNs: 0899-8418

Abstract

Abstract: Accurate spatial distribution information of rainfall is essential to rainfall‐induced hazard predictions and statistical interpolation methods may serve as a useful tool to produce a detailed distribution from coarse data sources. Although numerous comparison studies about different interpolation methods have been conducted on irregular rain‐gauge networks, there is a need to perform such work on the increasingly available gridded rainfall data. Carried out in the Emilia‐Romagna region (Italy) from 2008 to 2018, this study aims to examine accurate and appropriate interpolation methods to produce finer rainfall surface maps based on the 0.25° × 0.25° ERA5 gridded precipitation datasets. Five interpolation techniques, namely Thiessen polygons, Inverse Distance Weighting (IDW), Thin Plate Spline (TPS), Ordinary Kriging (OK) and ordinary Co‐Kriging (CoK), have been selected and compared at different time scales (annual, monthly and annual maximum daily precipitation). To assess the accuracy, the leave‐one‐out‐cross‐validation test was used by using the indexes of Bias, correlation coefficient, the Nash‐Sutcliffe Efficiency, Root Mean Square Error and the Kling‐Gupta Efficiency (KGE). Additionally, visual inspections are employed to evaluate the plausibility of the interpolated maps. Results show: (a) All five interpolation methods have certain capabilities to improve spatial resolution, but they fail on accuracy at the daily scale. The OK generally outperforms the other four methods, while TPS shows better performance through the visual inspection at the monthly scale; (b) Unlike in the case of the interpolation using conventional point‐based rain‐gauge data, the multivariate method CoK is inferior to the univariate ones and the p ‐power of the IDW also differs and (c) Winter and spring results are better than those of summer and autumn. This study has provided useful guidance on choosing suitable rainfall interpolation methods for gridded datasets, which can be expanded in other regions and data sources to explore the generality of the conclusions. Abstract : Based on ERA5 rainfall datasets, this study conducts a novel exploration of the applicability of interpolations methods for gridded rainfall products from accuracy and plausibility at three time scales. Unlike conventional rain‐gauge data, the CoK is inferior to the univariate ones and the p ‐value of the IDW differs for grid datasets. The OK generally outperforms others, while TPS shows better visual performance at monthly scale and in extreme events. Winter and spring results precede those of others.