New gridded dataset of rainfall erosivity (1950–2020) on the Tibetan Plateau
<p>The risk of water erosion on the Tibetan Plateau (TP), a typical fragile ecological area, is increasing with climate change. A rainfall erosivity map is useful for understanding the spatiotemporal pattern of rainfall erosivity and identifying hot spots of soil erosion. This study generates...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2022-06-01
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| Series: | Earth System Science Data |
| Online Access: | https://essd.copernicus.org/articles/14/2681/2022/essd-14-2681-2022.pdf |
| _version_ | 1817969089691254784 |
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| author | Y. Chen X. Duan M. Ding W. Qi T. Wei J. Li J. Li Y. Xie |
| author_facet | Y. Chen X. Duan M. Ding W. Qi T. Wei J. Li J. Li Y. Xie |
| author_sort | Y. Chen |
| collection | DOAJ |
| description | <p>The risk of water erosion on the Tibetan Plateau (TP), a typical
fragile ecological area, is increasing with climate change. A rainfall
erosivity map is useful for understanding the spatiotemporal pattern of
rainfall erosivity and identifying hot spots of soil erosion. This study
generates an annual gridded rainfall erosivity dataset on a 0.25<span class="inline-formula"><sup>∘</sup></span>
grid for the TP in 1950–2020. The 1 min precipitation observations at 1787 weather stations for 7 years and 0.25<span class="inline-formula"><sup>∘</sup></span> hourly European Center for
Medium-Range Weather Forecasts Reanalysis 5 (ERA5) precipitation data for 71 years are employed in this study. Our results indicate that the ERA5-based
estimates have a marked tendency to underestimate annual rainfall erosivity
when compared to the station-based estimates, because of the systematic
biases of ERA5 precipitation data including the large underestimation of the
maximum contiguous 30 min peak intensity and relatively slight
overestimation of event erosive precipitation amounts. The multiplier factor
map over the TP, which was generated by the inverse distance-weighted method
based on the relative changes between the available station-based annual
rainfall erosivity grid values and the corresponding ERA5-based values, was
employed to correct the ERA5-based annual rainfall erosivity and then
reconstruct the annual rainfall erosivity dataset. The multiyear average
correction coefficient over the TP between the station-based annual rainfall
erosivity values and the newly released data is 0.67. In addition, the
probability density and various quantile values of the new data are
generally consistent with the station-based values. The data offer a view
of large-scale spatiotemporal variability in the rainfall erosivity and
address the growing need for information to predict rainfall-induced
hazards over the TP. The dataset is available from the National Tibetan
Plateau/Third Pole Environment Data Center
(<a href="https://doi.org/10.11888/Terre.tpdc.271833">https://doi.org/10.11888/Terre.tpdc.271833</a>; Chen, 2021).</p> |
| first_indexed | 2024-04-13T20:16:03Z |
| format | Article |
| id | doaj.art-1005ec88804244b696150c2088a7b578 |
| institution | Directory Open Access Journal |
| issn | 1866-3508 1866-3516 |
| language | English |
| last_indexed | 2024-04-13T20:16:03Z |
| publishDate | 2022-06-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Earth System Science Data |
| spelling | doaj.art-1005ec88804244b696150c2088a7b5782022-12-22T02:31:41ZengCopernicus PublicationsEarth System Science Data1866-35081866-35162022-06-01142681269510.5194/essd-14-2681-2022New gridded dataset of rainfall erosivity (1950–2020) on the Tibetan PlateauY. Chen0X. Duan1M. Ding2W. Qi3T. Wei4J. Li5J. Li6Y. Xie7State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, ChinaInstitute of International Rivers and Eco-security, Yunnan University, Kunming, 650091, ChinaState Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, ChinaState Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, ChinaState Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, ChinaState Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, ChinaCMA Earth System Modeling and Prediction Centre, Beijing, 100081, ChinaState Key Laboratory of Earth Surface Processes and Resources Ecology, Faculty of Geographic Science, Beijing Normal University, Beijing, 100875, China<p>The risk of water erosion on the Tibetan Plateau (TP), a typical fragile ecological area, is increasing with climate change. A rainfall erosivity map is useful for understanding the spatiotemporal pattern of rainfall erosivity and identifying hot spots of soil erosion. This study generates an annual gridded rainfall erosivity dataset on a 0.25<span class="inline-formula"><sup>∘</sup></span> grid for the TP in 1950–2020. The 1 min precipitation observations at 1787 weather stations for 7 years and 0.25<span class="inline-formula"><sup>∘</sup></span> hourly European Center for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) precipitation data for 71 years are employed in this study. Our results indicate that the ERA5-based estimates have a marked tendency to underestimate annual rainfall erosivity when compared to the station-based estimates, because of the systematic biases of ERA5 precipitation data including the large underestimation of the maximum contiguous 30 min peak intensity and relatively slight overestimation of event erosive precipitation amounts. The multiplier factor map over the TP, which was generated by the inverse distance-weighted method based on the relative changes between the available station-based annual rainfall erosivity grid values and the corresponding ERA5-based values, was employed to correct the ERA5-based annual rainfall erosivity and then reconstruct the annual rainfall erosivity dataset. The multiyear average correction coefficient over the TP between the station-based annual rainfall erosivity values and the newly released data is 0.67. In addition, the probability density and various quantile values of the new data are generally consistent with the station-based values. The data offer a view of large-scale spatiotemporal variability in the rainfall erosivity and address the growing need for information to predict rainfall-induced hazards over the TP. The dataset is available from the National Tibetan Plateau/Third Pole Environment Data Center (<a href="https://doi.org/10.11888/Terre.tpdc.271833">https://doi.org/10.11888/Terre.tpdc.271833</a>; Chen, 2021).</p>https://essd.copernicus.org/articles/14/2681/2022/essd-14-2681-2022.pdf |
| spellingShingle | Y. Chen X. Duan M. Ding W. Qi T. Wei J. Li J. Li Y. Xie New gridded dataset of rainfall erosivity (1950–2020) on the Tibetan Plateau Earth System Science Data |
| title | New gridded dataset of rainfall erosivity (1950–2020) on the Tibetan Plateau |
| title_full | New gridded dataset of rainfall erosivity (1950–2020) on the Tibetan Plateau |
| title_fullStr | New gridded dataset of rainfall erosivity (1950–2020) on the Tibetan Plateau |
| title_full_unstemmed | New gridded dataset of rainfall erosivity (1950–2020) on the Tibetan Plateau |
| title_short | New gridded dataset of rainfall erosivity (1950–2020) on the Tibetan Plateau |
| title_sort | new gridded dataset of rainfall erosivity 1950 2020 on the tibetan plateau |
| url | https://essd.copernicus.org/articles/14/2681/2022/essd-14-2681-2022.pdf |
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