Evaluating the GPCC Full Data Daily Analysis Version 2018 through ETCCDI indices and comparison with station observation
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ORIGINAL PAPER
Evaluating the GPCC Full Data Daily Analysis Version 2018 through ETCCDI indices and comparison with station observations over mainland of China Yu Yu 1
&
Udo Schneider 2 & Su Yang 1 & Andreas Becker 2 & Zhihua Ren 1
Received: 9 September 2019 / Accepted: 7 August 2020 # The Author(s) 2020
Abstract The new 1° × 1° resolution global Full Data Daily Analysis Version 2018 published by the Global Precipitation Climatology Centre (GPCC) of Deutscher Wetterdienst was compared with an analysis of the measurements from the national dataset over the mainland of China with regard to four of the 27 ETCCDI indices (http://etccdi.pacificclimate.org/list_27_indices.shtml) commonly used to determine extreme precipitation (Rx5day, R10mm, CDD and SDII). After extreme value check, integrity check, and homogeneity check, the observations from 2327 surface stations covering the years from 1982 to 2016 fulfilled the criteria for the evaluation. The in situ daily precipitation data were interpolated onto a 1° × 1° grid over the mainland of China by employing Shepard’s angular and distance weighting algorithm. The four aforementioned indices were then calculated on the national station–based analysis being referred to as STA. Moreover, the aforementioned gridded GPCC Full Data Daily product was directly utilized to calculate the same indices (FDDA). The China national means of Rx5day, R10mm, CDD and SDII calculated from FDDA and STA had similar variations and trends with high correlation coefficients, and the mean biases between FDDA and STA were 2.5 mm, 1.2 days, 0.0 day and 0.3 mm respectively. The trends of Rx5day, R10mm and SDII are increasing, whereas the trend of CDD is negative. The distributions of the grid mean and the grid trends of indices over China from FDDA and STA show similar patterns too, indicating that the FDDA shows a surprisingly high fidelity in reproducing almost the same patterns in the four ETCCDI indices chosen compared with the STA-based analysis.
1 Introduction Precipitation is an essential climate variable to assess the fresh water supply of a region or nation. Therefore, its long-term changes are of high relevance for the public and the government in charge. In order to improve the understanding of the global water cycle, the Global Precipitation Climatology Centre (GPCC) inaugurated at Deutscher Wetterdienst in 1989 on request of the World Meteorological Organization (WMO) has successively developed a series of global grid products backward to 1891 with optional spatial resolutions. These precipitation analysis datasets are based on all available
* Andreas Becker [email protected] 1
National Meteorological Information Centre, China Meteorological Administration, Beijing 100081, China
2
Global Precipitation Climatology Centre (GPCC), Deutscher Wetterdienst, 63067 Offenbach am Main, Germany
daily and monthly in situ gauge measurements, processed by GPCC’s own semiautomatic data quality control system (Schneider et al. 2014). The products are useful for a number of applications ra
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