A Non‐Sigmoidal‐Curve‐Dependent Dynamic Threshold Method Improves Precipitation Phase Partitioning in the Northern Hemisphere
Abstract Given the significant impact of precipitation phase transitions on water and energy balances, accurate phase partitioning is essential for hydrological modeling. Many commonly used precipitation phase partitioning methods (PPMs) rely on sigmoidal curve assumptions to determine thresholds, l...
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Wiley
2025-04-01
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| Series: | Water Resources Research |
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| Online Access: | https://doi.org/10.1029/2024WR038636 |
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| author | Lina Liu Liping Zhang Qin Zhang Gangsheng Wang Zhiling Zhou Xiao Li Zhenyu Tang |
| author_facet | Lina Liu Liping Zhang Qin Zhang Gangsheng Wang Zhiling Zhou Xiao Li Zhenyu Tang |
| author_sort | Lina Liu |
| collection | DOAJ |
| description | Abstract Given the significant impact of precipitation phase transitions on water and energy balances, accurate phase partitioning is essential for hydrological modeling. Many commonly used precipitation phase partitioning methods (PPMs) rely on sigmoidal curve assumptions to determine thresholds, leading to biased partitioning results. Here we developed a non‐sigmoidal‐curve‐dependent dynamic threshold method (NSDT) to establish time‐varying and spatially varying thresholds for classifying precipitation into rain, snow, and sleet in the Northern Hemisphere. The NSDT avoids curve‐fitting errors by directly calculating thresholds from snowfall and rainfall frequency curves. In this method, relative humidity and elevation are the two most influential variables to precipitation phase, and single‐threshold and dual‐threshold strategies are employed separately across different relative humidity ranges. The results show that station thresholds derived from NSDT have marked spatial variability. Furthermore, the NSDT performs well and robustly, with accuracy exceeding 80% over the wet‐bulb temperature range [−10°C, 10°C] at each elevation range, relative humidity subinterval, and sub‐time period. The NSDT outperforms six commonly used PPMs, especially at high elevations. Regarding the wet‐bulb temperature range of [−4°C, 4°C], NSDT exhibits accuracy improvements ranging from 1.0% to 11.8% (0.4%–14.5%) across all elevation (relative humidity) subintervals compared to other PPMs. Overall, the NSDT method developed herein improves precipitation phase partitioning, which is expected to enhance the simulation accuracy of land surface models and hydrological models and provide a theoretical basis for a more accurate understanding of hydrological processes. |
| format | Article |
| id | doaj-art-78836067968d49f89d05c2a3a290765a |
| institution | OA Journals |
| issn | 0043-1397 1944-7973 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Wiley |
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| series | Water Resources Research |
| spelling | doaj-art-78836067968d49f89d05c2a3a290765a2025-08-20T02:36:42ZengWileyWater Resources Research0043-13971944-79732025-04-01614n/an/a10.1029/2024WR038636A Non‐Sigmoidal‐Curve‐Dependent Dynamic Threshold Method Improves Precipitation Phase Partitioning in the Northern HemisphereLina Liu0Liping Zhang1Qin Zhang2Gangsheng Wang3Zhiling Zhou4Xiao Li5Zhenyu Tang6State Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan ChinaState Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan ChinaChangjiang River Scientific Research Institute Changjiang Water Resources Commission Wuhan ChinaState Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan ChinaState Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan ChinaState Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan ChinaState Key Laboratory of Water Resources Engineering and Management Wuhan University Wuhan ChinaAbstract Given the significant impact of precipitation phase transitions on water and energy balances, accurate phase partitioning is essential for hydrological modeling. Many commonly used precipitation phase partitioning methods (PPMs) rely on sigmoidal curve assumptions to determine thresholds, leading to biased partitioning results. Here we developed a non‐sigmoidal‐curve‐dependent dynamic threshold method (NSDT) to establish time‐varying and spatially varying thresholds for classifying precipitation into rain, snow, and sleet in the Northern Hemisphere. The NSDT avoids curve‐fitting errors by directly calculating thresholds from snowfall and rainfall frequency curves. In this method, relative humidity and elevation are the two most influential variables to precipitation phase, and single‐threshold and dual‐threshold strategies are employed separately across different relative humidity ranges. The results show that station thresholds derived from NSDT have marked spatial variability. Furthermore, the NSDT performs well and robustly, with accuracy exceeding 80% over the wet‐bulb temperature range [−10°C, 10°C] at each elevation range, relative humidity subinterval, and sub‐time period. The NSDT outperforms six commonly used PPMs, especially at high elevations. Regarding the wet‐bulb temperature range of [−4°C, 4°C], NSDT exhibits accuracy improvements ranging from 1.0% to 11.8% (0.4%–14.5%) across all elevation (relative humidity) subintervals compared to other PPMs. Overall, the NSDT method developed herein improves precipitation phase partitioning, which is expected to enhance the simulation accuracy of land surface models and hydrological models and provide a theoretical basis for a more accurate understanding of hydrological processes.https://doi.org/10.1029/2024WR038636precipitation phase partitioningsigmoidal curverelative humidityelevationdynamic threshold method |
| spellingShingle | Lina Liu Liping Zhang Qin Zhang Gangsheng Wang Zhiling Zhou Xiao Li Zhenyu Tang A Non‐Sigmoidal‐Curve‐Dependent Dynamic Threshold Method Improves Precipitation Phase Partitioning in the Northern Hemisphere Water Resources Research precipitation phase partitioning sigmoidal curve relative humidity elevation dynamic threshold method |
| title | A Non‐Sigmoidal‐Curve‐Dependent Dynamic Threshold Method Improves Precipitation Phase Partitioning in the Northern Hemisphere |
| title_full | A Non‐Sigmoidal‐Curve‐Dependent Dynamic Threshold Method Improves Precipitation Phase Partitioning in the Northern Hemisphere |
| title_fullStr | A Non‐Sigmoidal‐Curve‐Dependent Dynamic Threshold Method Improves Precipitation Phase Partitioning in the Northern Hemisphere |
| title_full_unstemmed | A Non‐Sigmoidal‐Curve‐Dependent Dynamic Threshold Method Improves Precipitation Phase Partitioning in the Northern Hemisphere |
| title_short | A Non‐Sigmoidal‐Curve‐Dependent Dynamic Threshold Method Improves Precipitation Phase Partitioning in the Northern Hemisphere |
| title_sort | non sigmoidal curve dependent dynamic threshold method improves precipitation phase partitioning in the northern hemisphere |
| topic | precipitation phase partitioning sigmoidal curve relative humidity elevation dynamic threshold method |
| url | https://doi.org/10.1029/2024WR038636 |
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