Validation of DSDs of GPM DPR with Ground-Based Disdrometers over the Tianshan Region, China
The Tianshan Mountains are known as the “Water Tower of Central Asia” and are of significant strategic importance for Xinjiang as well as the Central Asian region. Accurately monitoring the spatiotemporal distribution of precipitation in the Tianshan Mountains is crucial for understanding global wat...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/1/79 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841549031370653696 |
|---|---|
| author | Xinyu Lu Xiuqin Wang Cheng Li Yan Liu Yong Zeng Hong Huo |
| author_facet | Xinyu Lu Xiuqin Wang Cheng Li Yan Liu Yong Zeng Hong Huo |
| author_sort | Xinyu Lu |
| collection | DOAJ |
| description | The Tianshan Mountains are known as the “Water Tower of Central Asia” and are of significant strategic importance for Xinjiang as well as the Central Asian region. Accurately monitoring the spatiotemporal distribution of precipitation in the Tianshan Mountains is crucial for understanding global water cycles and climate change. Raindrop Size Distribution (DSD) parameters play an important role in improving quantitative precipitation estimation with radar and understanding microphysical precipitation processes. In this study, DSD parameters in the Tianshan Mountains were evaluated on the basis of Global Precipitation Measurement mission (GPM) dual-frequency radar data (DPR) and ground-based laser disdrometer observations from 2019 to 2024. With the disdrometer observations as the true values, we performed spatiotemporal matching between the satellite radar and laser disdrometer data. The droplet spectrum parameters retrieved with the GPM dual-frequency radar system were compared with those calculated from the laser disdrometer observations. The reflectivity observations from the GPM DPR in both the Ku and Ka bands (ZKu and ZKa) were greater than the actual observations, with ZKa displaying a greater degree of overestimation than ZKu. In the applied single-frequency retrieval algorithm (SFA), the rainfall parameters retrieved from the Ka band outperformed those retrieved from the Ku band, indicating that the Ka band has stronger detection capability in the Tianshan Mountains area, where light rain predominates. The dual-frequency ratio (DFR), i.e., the differences in the reflectivity of the raindrop spectra obtained from both the Ku and Ka bands, fluctuated more greatly than those of the GPM DPR. DFR is a monotonically increasing function of the mass-weighted mean drop diameter (Dm). Rainfall rate (R) and Dm exhibited a strong positive correlation, and the fitted curve followed a power function distribution. |
| format | Article |
| id | doaj-art-e57a755961be4cb283a179a0a76b0b92 |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-e57a755961be4cb283a179a0a76b0b922025-01-10T13:20:09ZengMDPI AGRemote Sensing2072-42922024-12-011717910.3390/rs17010079Validation of DSDs of GPM DPR with Ground-Based Disdrometers over the Tianshan Region, ChinaXinyu Lu0Xiuqin Wang1Cheng Li2Yan Liu3Yong Zeng4Hong Huo5Institute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, ChinaMeteorological Information Center of Xinjiang Uygur Autonomous Region, Urumqi 830002, ChinaMeteorological Information Center of Xinjiang Uygur Autonomous Region, Urumqi 830002, ChinaInstitute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, ChinaInstitute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, ChinaInstitute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, ChinaThe Tianshan Mountains are known as the “Water Tower of Central Asia” and are of significant strategic importance for Xinjiang as well as the Central Asian region. Accurately monitoring the spatiotemporal distribution of precipitation in the Tianshan Mountains is crucial for understanding global water cycles and climate change. Raindrop Size Distribution (DSD) parameters play an important role in improving quantitative precipitation estimation with radar and understanding microphysical precipitation processes. In this study, DSD parameters in the Tianshan Mountains were evaluated on the basis of Global Precipitation Measurement mission (GPM) dual-frequency radar data (DPR) and ground-based laser disdrometer observations from 2019 to 2024. With the disdrometer observations as the true values, we performed spatiotemporal matching between the satellite radar and laser disdrometer data. The droplet spectrum parameters retrieved with the GPM dual-frequency radar system were compared with those calculated from the laser disdrometer observations. The reflectivity observations from the GPM DPR in both the Ku and Ka bands (ZKu and ZKa) were greater than the actual observations, with ZKa displaying a greater degree of overestimation than ZKu. In the applied single-frequency retrieval algorithm (SFA), the rainfall parameters retrieved from the Ka band outperformed those retrieved from the Ku band, indicating that the Ka band has stronger detection capability in the Tianshan Mountains area, where light rain predominates. The dual-frequency ratio (DFR), i.e., the differences in the reflectivity of the raindrop spectra obtained from both the Ku and Ka bands, fluctuated more greatly than those of the GPM DPR. DFR is a monotonically increasing function of the mass-weighted mean drop diameter (Dm). Rainfall rate (R) and Dm exhibited a strong positive correlation, and the fitted curve followed a power function distribution.https://www.mdpi.com/2072-4292/17/1/79DPRDSDground-based validationdisdrometerTianshan |
| spellingShingle | Xinyu Lu Xiuqin Wang Cheng Li Yan Liu Yong Zeng Hong Huo Validation of DSDs of GPM DPR with Ground-Based Disdrometers over the Tianshan Region, China Remote Sensing DPR DSD ground-based validation disdrometer Tianshan |
| title | Validation of DSDs of GPM DPR with Ground-Based Disdrometers over the Tianshan Region, China |
| title_full | Validation of DSDs of GPM DPR with Ground-Based Disdrometers over the Tianshan Region, China |
| title_fullStr | Validation of DSDs of GPM DPR with Ground-Based Disdrometers over the Tianshan Region, China |
| title_full_unstemmed | Validation of DSDs of GPM DPR with Ground-Based Disdrometers over the Tianshan Region, China |
| title_short | Validation of DSDs of GPM DPR with Ground-Based Disdrometers over the Tianshan Region, China |
| title_sort | validation of dsds of gpm dpr with ground based disdrometers over the tianshan region china |
| topic | DPR DSD ground-based validation disdrometer Tianshan |
| url | https://www.mdpi.com/2072-4292/17/1/79 |
| work_keys_str_mv | AT xinyulu validationofdsdsofgpmdprwithgroundbaseddisdrometersoverthetianshanregionchina AT xiuqinwang validationofdsdsofgpmdprwithgroundbaseddisdrometersoverthetianshanregionchina AT chengli validationofdsdsofgpmdprwithgroundbaseddisdrometersoverthetianshanregionchina AT yanliu validationofdsdsofgpmdprwithgroundbaseddisdrometersoverthetianshanregionchina AT yongzeng validationofdsdsofgpmdprwithgroundbaseddisdrometersoverthetianshanregionchina AT honghuo validationofdsdsofgpmdprwithgroundbaseddisdrometersoverthetianshanregionchina |