| 19 Jun 2026
A multidimensional daily precipitation dataset (1998-2024) over the Third Pole with uncertainty estimates and precipitation phase information
Abstract. Accurate precipitation data for the Tibetan Plateau (TP) is critical for understanding regional water resources and global climate dynamics. However, existing datasets struggle with observational bottlenecks due to complex terrain and high precipitation variability. Here, we introduce the CRISP (Conformal Regression and Integrated Stacking for Precipitation) dataset, providing a continuous, 27-year (1998-2024) daily precipitation record at a 0.1° spatial resolution for the TP. Unlike conventional statistical datasets, CRISP integrates physical atmospheric conditions and terrain features into a machine-learning framework. The CRISP dataset effectively identifies false drizzle signals commonly seen in reanalysis data without missing most real rainfall events. Furthermore, CRISP can provide reliable 90% uncertainty intervals that adaptively adjust to the intensity of rainfall compared to other datasets, and it explicitly classifies precipitation into rain, snow, and mixed phases to directly support cryospheric research. The independent validations indicate that CRISP shows potential in reducing inconsistencies associated with the “Third Pole precipitation paradox” (Miao et al., 2024). By providing consistent precipitation estimates together with uncertainty information and phase classification, CRISP offers a valuable basis for hydroclimatic research over the Third Pole and its downstream regions. The CRISP dataset is openly available at (https://doi.org/10.11888/Atmos.tpdc.303469; Yong & Lyu, 2026).
A multidimensional daily precipitation dataset (1998-2024) over the Third Pole with uncertainty estimates and precipitation phase information
This study presents a valuable precipitation dataset over the Third Pole region, with the unique capability of providing precipitation amount, precipitation phase, and associated uncertainty estimates. Given the critical importance of accurate precipitation information for understanding hydrological processes and climate variability over the Tibetan Plateau, this work is highly relevant and potentially useful for the community. Overall, I support publication of this manuscript after revision. However, several aspects should be further improved to enhance the scientific rigor and impact of this study.
1. A more comprehensive comparison with existing precipitation datasets is needed.
The authors should provide a more thorough review and systematic comparison with existing precipitation datasets developed for the Tibetan Plateau and surrounding regions. Several recently developed datasets should be considered, including AIMERG, a new Asian precipitation dataset (0.1°, half-hourly, 2000–2015) generated by calibrating GPM-era IMERG using APHRODITE observations; AERA5-Asia, a long-term Asian precipitation dataset (0.1°, hourly, 1951–2015) developed by constraining ERA5-Land precipitation with APHRODITE-based total volume control; and GMCP, a fully global multisource merging and calibration precipitation dataset (1-hourly, 0.1°, 2000–present).
These datasets have achieved relatively high temporal resolution (e.g., hourly or sub-hourly), and a comprehensive assessment against these products would help better demonstrate the advantages and uniqueness of the proposed CRISP dataset. In addition, the authors should discuss whether the current daily temporal resolution could be further improved to hourly resolution, which would significantly enhance its applicability for hydrological and cryospheric studies.
2. The validation of precipitation phase information requires further strengthening.
One of the major strengths and unique contributions of this study is the explicit classification of precipitation phases, including rain, snow, and mixed precipitation. However, the current validation of precipitation phase information appears relatively limited. More comprehensive evaluations using independent observations (e.g., ground-based precipitation phase observations, weather stations, snow observations, or available remote sensing products) are recommended. The authors should provide more quantitative evidence demonstrating the reliability of the precipitation phase classification, particularly over complex terrain and high-altitude regions where phase transitions are highly variable.
3.The manuscript presentation and visualization should be further improved.
The writing, structure, and figures require additional refinement. The authors should further emphasize the unique characteristics and scientific contributions of the CRISP dataset, particularly its advantages in simultaneously providing precipitation estimates, uncertainty information, and precipitation phase classification. Clearer comparisons with existing datasets and more effective visualization of the dataset’s distinctive features would substantially improve the readability and impact of the manuscript.
Overall, this study provides an important contribution by developing a multidimensional precipitation dataset for the Third Pole region. With strengthened literature comparisons, more comprehensive validation of precipitation phase information, and improved presentation, the manuscript would become a valuable resource for hydrological, cryospheric, and climate research communities.