| Item | Content |
|---|---|
| Title | Precipitation Trends Analysis Using Gridded Dynamic Sampling Zones Case Study Yangtze Delta Megalopolis |
| Author | X Liu and D Fu and C Zevenbergen and M Yu and AJ Kumar |
| Journal | Frontiers in Earth Science |
| Year | 2022 |
| Volume | 10 |
| Issue | / |
| Pages | 917069 |
| Abstract | As a result of the fast growth of remote sensing and data assimilation technology, many global land use land cover (LULC) and climate reanalysis data sets have been used to advance our understanding of climate and environmental change. This paper investigates the precipitation variations of the Yangtze Delta Megalopolis by using precipitation reanalysis data under conditions of dynamic urban sprawl. Compared with current precipitation characteristic analyses, which are often based on a limited number of ground rainfall stations, the approach followed in this study comprises a grid-based statistical method using large sets of samples with a uniform distribution and a same representative grid area. This novel approach of dynamic sampling is applied in this study to overcome the temporal and spatial inconsistency of stationary sampling. This approach allows to examine the impact of urbanization on regional precipitation characteristics. The Yangtze Delta Megalopolis (YDM) region, one of the most developed regions in China, was selected as a case study to evaluate the impact of urbanization on subsequent precipitation features. The results reveal that the annual total precipitation (TP) and the maximum daily precipitation (MDP) in both urban and non-urban areas of the YDM region generally have increased during the past 30years. Hence, the region has become increasingly humid. Extrema of annual MDP and TP show obvious spatial characteristics, in which most maxima are located in the southern part of YDM while minima are more concentrated in the northern part. This newly developed approach has potentials for application in … |
| Cited by | / |
| Url | https://www.frontiersin.org/articles/10.3389/feart.2022.917069/full |
| Achive | https://www.frontiersin.org/articles/10.3389/feart.2022.917069/pdf |
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