An algorithm to improve satellite-only precipitation estimates over the Tibetan Plateau
(2026) In Atmospheric Research 339.- Abstract
Accurate rainfall data is essential for understanding the water cycle and monitoring climate change. However, precipitation estimates from satellite-only retrievals such as the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) Early Run (IMERG-E), often contain large errors. These errors limit their usefulness for scientific studies and practical applications. To address this issue, we develop a new algorithm called Dual-Timescale Minimum Error (DTME), which combines advanced statistical techniques including the (categorical) double instrumental variable method, inverse errors-based combination, and linear scaling. The DTME algorithm is applied to improve the accuracy of daily satellite-only... (More)
Accurate rainfall data is essential for understanding the water cycle and monitoring climate change. However, precipitation estimates from satellite-only retrievals such as the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) Early Run (IMERG-E), often contain large errors. These errors limit their usefulness for scientific studies and practical applications. To address this issue, we develop a new algorithm called Dual-Timescale Minimum Error (DTME), which combines advanced statistical techniques including the (categorical) double instrumental variable method, inverse errors-based combination, and linear scaling. The DTME algorithm is applied to improve the accuracy of daily satellite-only precipitation data by integrating it with daily and monthly global gauge-based datasets. Taking IMERG-E as an example, this study provides a new precipitation product IMERG-D (0.1°/1 d, 2001–2019) over the Tibetan Plateau, an area where accurate precipitation measurements are especially challenging due to its high altitude, complex climate, and sparse station network. Using 116 independent station observations for performance evaluation, statistical scores show that the algorithm significantly enhances the performance of IMERG-E across multiple timescales, achieving higher correlation (increasing from 0.63 to 0.76), lower errors (decreasing from 3.59 to 2.63 mm/day), and better detection rates (rising from 0.49 to 0.58). Importantly, IMERG-D performs better than the bias-corrected IMERG Final Run and gauge-adjusted Global Satellite Mapping of Precipitation (GSMaP) products. These results demonstrate the effectiveness of the DTME algorithm in improving the reliability of satellite-only precipitation estimates in the alpine region with rare stations. Therefore, the algorithm shows promise for broader application of satellite-only precipitation product in hydrological and meteorological fields, such as hydrological modelling and climate assessments.
(Less)
- author
- Wei, Linyong LU ; Jiang, Shanhu ; Ren, Liliang ; Hua, Zulin ; Zhang, Linqi ; Zeng, Liping and Duan, Zheng LU
- organization
- publishing date
- 2026-09
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Dual-Timescale Minimum Error (DTME) algorithm, GSMaP, IMERG, Satellite-only precipitation estimates, Tibetan Plateau
- in
- Atmospheric Research
- volume
- 339
- article number
- 109035
- publisher
- Elsevier
- external identifiers
-
- scopus:105037753267
- ISSN
- 0169-8095
- DOI
- 10.1016/j.atmosres.2026.109035
- language
- English
- LU publication?
- yes
- id
- d395fe90-024f-4932-bf57-572ef673e55c
- date added to LUP
- 2026-08-19 11:33:42
- date last changed
- 2026-08-19 12:00:50
@article{d395fe90-024f-4932-bf57-572ef673e55c,
abstract = {{<p>Accurate rainfall data is essential for understanding the water cycle and monitoring climate change. However, precipitation estimates from satellite-only retrievals such as the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) Early Run (IMERG-E), often contain large errors. These errors limit their usefulness for scientific studies and practical applications. To address this issue, we develop a new algorithm called Dual-Timescale Minimum Error (DTME), which combines advanced statistical techniques including the (categorical) double instrumental variable method, inverse errors-based combination, and linear scaling. The DTME algorithm is applied to improve the accuracy of daily satellite-only precipitation data by integrating it with daily and monthly global gauge-based datasets. Taking IMERG-E as an example, this study provides a new precipitation product IMERG-D (0.1°/1 d, 2001–2019) over the Tibetan Plateau, an area where accurate precipitation measurements are especially challenging due to its high altitude, complex climate, and sparse station network. Using 116 independent station observations for performance evaluation, statistical scores show that the algorithm significantly enhances the performance of IMERG-E across multiple timescales, achieving higher correlation (increasing from 0.63 to 0.76), lower errors (decreasing from 3.59 to 2.63 mm/day), and better detection rates (rising from 0.49 to 0.58). Importantly, IMERG-D performs better than the bias-corrected IMERG Final Run and gauge-adjusted Global Satellite Mapping of Precipitation (GSMaP) products. These results demonstrate the effectiveness of the DTME algorithm in improving the reliability of satellite-only precipitation estimates in the alpine region with rare stations. Therefore, the algorithm shows promise for broader application of satellite-only precipitation product in hydrological and meteorological fields, such as hydrological modelling and climate assessments.</p>}},
author = {{Wei, Linyong and Jiang, Shanhu and Ren, Liliang and Hua, Zulin and Zhang, Linqi and Zeng, Liping and Duan, Zheng}},
issn = {{0169-8095}},
keywords = {{Dual-Timescale Minimum Error (DTME) algorithm; GSMaP; IMERG; Satellite-only precipitation estimates; Tibetan Plateau}},
language = {{eng}},
publisher = {{Elsevier}},
series = {{Atmospheric Research}},
title = {{An algorithm to improve satellite-only precipitation estimates over the Tibetan Plateau}},
url = {{http://dx.doi.org/10.1016/j.atmosres.2026.109035}},
doi = {{10.1016/j.atmosres.2026.109035}},
volume = {{339}},
year = {{2026}},
}