A Dynamical Z-R Relationship for Precipitation Estimation Based on Radar Echo-Top Height Classification
Using echo-top height and hourly rainfall datasets, a new reflectivity-rainfall (Z-R) relationship is established in the present study for the radar-based quantitative precipitation estimation (RQPE), taking into account both the temporal evolution (dynamical) and the types of echoes (i.e., based on...
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| Language: | English |
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Wiley
2018-01-01
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| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2018/8202031 |
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| author | Wenxin Wu Haibo Zou Jiusheng Shan Shanshan Wu |
| author_facet | Wenxin Wu Haibo Zou Jiusheng Shan Shanshan Wu |
| author_sort | Wenxin Wu |
| collection | DOAJ |
| description | Using echo-top height and hourly rainfall datasets, a new reflectivity-rainfall (Z-R) relationship is established in the present study for the radar-based quantitative precipitation estimation (RQPE), taking into account both the temporal evolution (dynamical) and the types of echoes (i.e., based on echo-top height classification). The new Z-R relationship is then applied to derive the RQPE over the middle and lower reaches of Yangtze River for two short-time intense rainfall cases in summer (2200 UTC 1 June 2016 and 2200 UTC 18 June 2016) and one stratiform rainfall case in winter (0000 UTC 15 December 2017), and then the comparative analyses between the RQPE and the RQPEs derived by the other two methods (the fixed Z-R relationship and the dynamical Z-R relationship based on radar reflectivity classification) are accomplished. The results show that the RQPE from the new Z-R relationship is much closer to the observation than those from the other two methods because the new method simultaneously considers the echo intensity (reflecting the size and concentration of hydrometers to a certain extent) and the echo-top height (reflecting the updraft to a certain extent). Two statistics of 720 rainfall events in summer (April to June 2017) and 50 rainfall events in winter (December 2017) over the same region show that the correlation coefficient (root-mean-squared error and relative error) between RQPE derived by the new Z-R relationship and observation is significantly increased (decreased) compared to the other two Z-R relationships. Besides, the new Z-R relationship is also good at estimating rainfall with different intensities as compared to the other two methods, especially for the intense rainfall. |
| format | Article |
| id | doaj-art-b6aa422093194fd08b76797a3f7dbd97 |
| institution | Kabale University |
| issn | 1687-9309 1687-9317 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
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| series | Advances in Meteorology |
| spelling | doaj-art-b6aa422093194fd08b76797a3f7dbd972025-02-03T01:26:31ZengWileyAdvances in Meteorology1687-93091687-93172018-01-01201810.1155/2018/82020318202031A Dynamical Z-R Relationship for Precipitation Estimation Based on Radar Echo-Top Height ClassificationWenxin Wu0Haibo Zou1Jiusheng Shan2Shanshan Wu3Meteorological Disaster Emergency Warning Centre of Jiangxi, Nanchang 330096, ChinaMeteorological Disaster Emergency Warning Centre of Jiangxi, Nanchang 330096, ChinaMeteorological Disaster Emergency Warning Centre of Jiangxi, Nanchang 330096, ChinaJiangxi Climate Centre, Nanchang 330096, ChinaUsing echo-top height and hourly rainfall datasets, a new reflectivity-rainfall (Z-R) relationship is established in the present study for the radar-based quantitative precipitation estimation (RQPE), taking into account both the temporal evolution (dynamical) and the types of echoes (i.e., based on echo-top height classification). The new Z-R relationship is then applied to derive the RQPE over the middle and lower reaches of Yangtze River for two short-time intense rainfall cases in summer (2200 UTC 1 June 2016 and 2200 UTC 18 June 2016) and one stratiform rainfall case in winter (0000 UTC 15 December 2017), and then the comparative analyses between the RQPE and the RQPEs derived by the other two methods (the fixed Z-R relationship and the dynamical Z-R relationship based on radar reflectivity classification) are accomplished. The results show that the RQPE from the new Z-R relationship is much closer to the observation than those from the other two methods because the new method simultaneously considers the echo intensity (reflecting the size and concentration of hydrometers to a certain extent) and the echo-top height (reflecting the updraft to a certain extent). Two statistics of 720 rainfall events in summer (April to June 2017) and 50 rainfall events in winter (December 2017) over the same region show that the correlation coefficient (root-mean-squared error and relative error) between RQPE derived by the new Z-R relationship and observation is significantly increased (decreased) compared to the other two Z-R relationships. Besides, the new Z-R relationship is also good at estimating rainfall with different intensities as compared to the other two methods, especially for the intense rainfall.http://dx.doi.org/10.1155/2018/8202031 |
| spellingShingle | Wenxin Wu Haibo Zou Jiusheng Shan Shanshan Wu A Dynamical Z-R Relationship for Precipitation Estimation Based on Radar Echo-Top Height Classification Advances in Meteorology |
| title | A Dynamical Z-R Relationship for Precipitation Estimation Based on Radar Echo-Top Height Classification |
| title_full | A Dynamical Z-R Relationship for Precipitation Estimation Based on Radar Echo-Top Height Classification |
| title_fullStr | A Dynamical Z-R Relationship for Precipitation Estimation Based on Radar Echo-Top Height Classification |
| title_full_unstemmed | A Dynamical Z-R Relationship for Precipitation Estimation Based on Radar Echo-Top Height Classification |
| title_short | A Dynamical Z-R Relationship for Precipitation Estimation Based on Radar Echo-Top Height Classification |
| title_sort | dynamical z r relationship for precipitation estimation based on radar echo top height classification |
| url | http://dx.doi.org/10.1155/2018/8202031 |
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