Hier finden Sie wissenschaftliche Publikationen aus den Fraunhofer-Instituten.

Spatiotemporal characteristics of extreme precipitation regimes in the Eastern Inland River Basin of Inner Mongolian Plateau, China

: Li, Wei; Duan, Limin; Luo, Yanyun; Liu, Tingxi; Scharaw, Buren

Fulltext urn:nbn:de:0011-n-5256044 (10 MByte PDF)
MD5 Fingerprint: e60c17588096cb24fcad5f6c16ba5e97
(CC) by
Created on: 9.1.2019

Water 10 (2018), No.1, Art. 35, 16 pp.
ISSN: 2073-4441
Journal Article, Electronic Publication
Fraunhofer IOSB ()

In this work, we use the gridded precipitation dataset (with a resolution of 0.5° × 0.5°) of the eastern part of inland river basin of Inner Mongolian Plateau from 1961–2015 as the basis and adopt the methods of climatic diagnosis (e.g., the Modified Mann-Kendall method, principal component analysis, and correlation analysis) to analyze the spatial and temporal variations of six extreme precipitation indices. Furthermore, we analyzed the relationship between El Niño–Southern Oscillation (ENSO) events and the observed extreme precipitation. The results indicated that the gridded dataset can be used to describe the precipitation distribution in our study area. In recent 55 years, the inter-annual variation trends of extreme precipitation indices are generally dominated by declination except for the maximum precipitation over five days (RX5DAY) and the heavy precipitation (R95P), in particular, the decreasing regions of consecutive dry days (CDD) accounts for 91% of the entire basin, 17.28% of which is showing the significant downward trend. Contrary to CDD, the spatial distribution of the other five indices is gradually decreasing from northeast to southwest, and the precipitation intensity (SDII) ranges from 3.8–5.3 mm·d−1, with relatively small spatial differences. To some extent, CDD and R95P can used to characterize the extreme precipitation regimes. Moreover, the number of days with heavy precipitation (RR10), SDII, and R95P are more susceptible to the ENSO events. In addition, the moderate El Niño event may increase the probability of CDD, while the La Niña events may increase the risk of the heavy rainfall regime in the study area.