Articles | Volume 13, issue 11
https://doi.org/10.5194/essd-13-5455-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-5455-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
26 Nov 2021
Data description paper |
| 26 Nov 2021
| 26 Nov 2021
A high-accuracy rainfall dataset by merging multiple satellites and dense gauges over the southern Tibetan Plateau for 2014–2019 warm seasons
Kunbiao Li
Department of Hydraulic Engineering, Tsinghua University, Beijing, China
Department of Hydraulic Engineering, Tsinghua University, Beijing, China
Mohd Yawar Ali Khan
Department of Hydrogeology, King Abdul-Aziz University, Jeddah, Saudi Arabia
Ran Xu
Department of Hydraulic Engineering, Tsinghua University, Beijing, China
Zhihua He
Centre for Hydrology, University of Saskatchewan, Saskatoon, SK S7N 5C8, Canada
Long Yang
School of Geography and Ocean Science, Nanjing University, Nanjing, China
Hui Lu
Department of Earth System Science, Tsinghua University, Beijing, China
Yingzhao Ma
Cooperative Institute for Research in the Atmosphere, Colorado State University, 1375 Campus Delivery, Fort Collins, CO 80523, USA
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Cited
20 citations as recorded by crossref.
- TPHiPr: a long-term (1979–2020) high-accuracy precipitation dataset (1∕30°, daily) for the Third Pole region based on high-resolution atmospheric modeling and dense observations Y. Jiang et al. 10.5194/essd-15-621-2023
- Mid-century change analysis of temperature and precipitation maxima in the Swat River Basin, Pakistan W. Ali et al. 10.3389/fenvs.2022.973759
- Deep learning-based multi-source precipitation merging for the Tibetan Plateau T. Nan et al. 10.1007/s11430-022-1050-2
- Evaluating the effectiveness of CHIRPS data for hydroclimatic studies H. Du et al. 10.1007/s00704-023-04721-9
- Spatiotemporal Evaluation and Estimation of Precipitation of Multi-Source Precipitation Products in Arid Areas of Northwest China—A Case Study of Tianshan Mountains X. Li et al. 10.3390/w14162566
- An assessment of gridded precipitation products over High Mountain Asia I. Dollan et al. 10.1016/j.ejrh.2024.101675
- Blending high-resolution satellite rainfall estimates over urban catchment using Bayesian Model Averaging approach W. Asfaw et al. 10.1016/j.ejrh.2022.101287
- Evaluation of accuracy for satellites rainfall datasets compared in ground stations: a case study of duhok governorate, Northern Iraq A. Al-Hussein et al. 10.1007/s40899-024-01158-4
- 基于深度学习的青藏高原多源降水融合 天. 南 et al. 10.1360/SSTe-2022-0077
- A ten-year (2012–2021) fine-resolution (1 km, hourly) precipitation dataset over southeastern Tibetan Plateau D. Li et al. 10.1038/s41597-025-04654-0
- Glaciers determine the sensitivity of hydrological processes to perturbed climate in a large mountainous basin on the Tibetan Plateau Y. Nan & F. Tian 10.5194/hess-28-669-2024
- Development of high resolution daily gridded precipitation and temperature dataset for potohar plateau of indus basin M. Khan et al. 10.1007/s00704-023-04626-7
- Improving the accuracy of reconstructed terrestrial water storage during the GRACE/GRACE-FO gap based on a new variable filter reconstruction model S. Yang et al. 10.1080/01431161.2023.2277162
- Quantifying the Reliability and Uncertainty of Satellite, Reanalysis, and Merged Precipitation Products in Hydrological Simulations over the Topographically Diverse Basin in Southwest China H. Lei et al. 10.3390/rs15010213
- Development of daily bias-corrected ensemble precipitation estimates over the Upper Indus Basin of the Hindukush-Karakoram-Himalaya K. Jamal et al. 10.2166/wcc.2023.202
- Quick Predictions of Onset Times and Rain Amounts from Monsoon Showers over Urban Built Environments S. Gumber & S. Ghosh 10.3390/atmos13030370
- How has the latest IMERG V07 improved the precipitation estimates and hydrologic utility over CONUS against IMERG V06? S. Zhu et al. 10.1016/j.jhydrol.2024.132257
- Global reconstruction of gridded aridity index and its spatial and temporal characterization from 2003 to 2022 J. Lu et al. 10.1080/17538947.2025.2473639
- A Downscaling–Merging Scheme for Monthly Precipitation Estimation with High Resolution Based on CBAM-ConvLSTM B. Tian et al. 10.3390/rs15184601
- A high-accuracy rainfall dataset by merging multiple satellites and dense gauges over the southern Tibetan Plateau for 2014–2019 warm seasons K. Li et al. 10.5194/essd-13-5455-2021
19 citations as recorded by crossref.
- TPHiPr: a long-term (1979–2020) high-accuracy precipitation dataset (1∕30°, daily) for the Third Pole region based on high-resolution atmospheric modeling and dense observations Y. Jiang et al. 10.5194/essd-15-621-2023
- Mid-century change analysis of temperature and precipitation maxima in the Swat River Basin, Pakistan W. Ali et al. 10.3389/fenvs.2022.973759
- Deep learning-based multi-source precipitation merging for the Tibetan Plateau T. Nan et al. 10.1007/s11430-022-1050-2
- Evaluating the effectiveness of CHIRPS data for hydroclimatic studies H. Du et al. 10.1007/s00704-023-04721-9
- Spatiotemporal Evaluation and Estimation of Precipitation of Multi-Source Precipitation Products in Arid Areas of Northwest China—A Case Study of Tianshan Mountains X. Li et al. 10.3390/w14162566
- An assessment of gridded precipitation products over High Mountain Asia I. Dollan et al. 10.1016/j.ejrh.2024.101675
- Blending high-resolution satellite rainfall estimates over urban catchment using Bayesian Model Averaging approach W. Asfaw et al. 10.1016/j.ejrh.2022.101287
- Evaluation of accuracy for satellites rainfall datasets compared in ground stations: a case study of duhok governorate, Northern Iraq A. Al-Hussein et al. 10.1007/s40899-024-01158-4
- 基于深度学习的青藏高原多源降水融合 天. 南 et al. 10.1360/SSTe-2022-0077
- A ten-year (2012–2021) fine-resolution (1 km, hourly) precipitation dataset over southeastern Tibetan Plateau D. Li et al. 10.1038/s41597-025-04654-0
- Glaciers determine the sensitivity of hydrological processes to perturbed climate in a large mountainous basin on the Tibetan Plateau Y. Nan & F. Tian 10.5194/hess-28-669-2024
- Development of high resolution daily gridded precipitation and temperature dataset for potohar plateau of indus basin M. Khan et al. 10.1007/s00704-023-04626-7
- Improving the accuracy of reconstructed terrestrial water storage during the GRACE/GRACE-FO gap based on a new variable filter reconstruction model S. Yang et al. 10.1080/01431161.2023.2277162
- Quantifying the Reliability and Uncertainty of Satellite, Reanalysis, and Merged Precipitation Products in Hydrological Simulations over the Topographically Diverse Basin in Southwest China H. Lei et al. 10.3390/rs15010213
- Development of daily bias-corrected ensemble precipitation estimates over the Upper Indus Basin of the Hindukush-Karakoram-Himalaya K. Jamal et al. 10.2166/wcc.2023.202
- Quick Predictions of Onset Times and Rain Amounts from Monsoon Showers over Urban Built Environments S. Gumber & S. Ghosh 10.3390/atmos13030370
- How has the latest IMERG V07 improved the precipitation estimates and hydrologic utility over CONUS against IMERG V06? S. Zhu et al. 10.1016/j.jhydrol.2024.132257
- Global reconstruction of gridded aridity index and its spatial and temporal characterization from 2003 to 2022 J. Lu et al. 10.1080/17538947.2025.2473639
- A Downscaling–Merging Scheme for Monthly Precipitation Estimation with High Resolution Based on CBAM-ConvLSTM B. Tian et al. 10.3390/rs15184601
Latest update: 30 Mar 2025
Short summary
Due to complex climate and topography, there is still a lack of a high-quality rainfall dataset for hydrological modeling over the Tibetan Plateau. This study aims to establish a high-accuracy daily rainfall product over the southern Tibetan Plateau through merging satellite rainfall estimates based on a high-density rainfall gauge network. Statistical and hydrological evaluation indicated that the new dataset outperforms the raw satellite estimates and several other products of similar types.
Due to complex climate and topography, there is still a lack of a high-quality rainfall dataset...
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