Investigation of an extreme rainfall event during 8–12 December 2018 over central Vietnam – Part 2: An evaluation of predictability using a time-lagged cloud-resolving ensemble system
<p>This is the second part of a two-part study that investigates an extreme rainfall event that occurred from 8 to 12 December 2018 over central Vietnam (referred to as the D18 event). In this part, the study aims to evaluate the practical predictability of the D18 event using the quantitative...
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| Format: | Article |
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Copernicus Publications
2025-08-01
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| Series: | Natural Hazards and Earth System Sciences |
| Online Access: | https://nhess.copernicus.org/articles/25/2803/2025/nhess-25-2803-2025.pdf |
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| author | C.-C. Wang D. V. Nguyen D. V. Nguyen T. V. Vu P. Thi Thanh Nga P.-Y. Chuang K. B. Truong |
| author_facet | C.-C. Wang D. V. Nguyen D. V. Nguyen T. V. Vu P. Thi Thanh Nga P.-Y. Chuang K. B. Truong |
| author_sort | C.-C. Wang |
| collection | DOAJ |
| description | <p>This is the second part of a two-part study that investigates an extreme rainfall event that occurred from 8 to 12 December 2018 over central Vietnam (referred to as the D18 event). In this part, the study aims to evaluate the practical predictability of the D18 event using the quantitative precipitation forecasts (QPFs) from a time-lagged cloud-resolving ensemble system. To do this, 29 time-lagged (8 d in forecast range) high-resolution (2.5 km) members were run, with the first member initialized at 12:00 UTC on 3 December and the last one at 12:00 UTC on 10 December 2018. Between the first and the last members are multiple members that were executed every 6 h. The evaluation results reveal that the cloud-resolving model (CReSS) predicted the rainfall fields in the short range (less than 3 d) well for 10 December (the rainiest day). Particularly, the CReSS model shows high skill in heavy-rainfall QPFs for this date with a similarity skill score (SSS) greater than 0.5 for both the last five members and the last nine members. The good results are due to the model having good predictions of relevant meteorological variables such as surface winds. However, the predictive skill is reduced at lead times longer than 3 d, and it is challenging to achieve good QPFs for rainfall thresholds greater than 100 mm at lead times longer than 6 d. These results also confirmed our scientific hypothesis that the cloud-resolving time-lagged ensemble system (using the CReSS model) improved the QPFs of this event in the short range. Furthermore, the results also demonstrated that a decent QPF can be made at a longer lead time (by a member initialized at 18:00 UTC on 4 December).</p>
<p>In addition, the ensemble-based sensitivity analysis (ESA) of 24 h rainfall in central Vietnam shows that it is highly sensitive to initial conditions, not only at lower levels but also at upper levels. The rainfall is sensitive to both kinematics and moisture convergence at low levels, and such sensitivities decrease with increasing lead time. The ESA also facilitates a better understanding of the mechanisms in the D18 event, implying that it is meaningful to apply ESA to control initial conditions in the future.</p> |
| format | Article |
| id | doaj-art-0f2c2531ce7a4ecaa21cfb0efa5eeb3b |
| institution | Kabale University |
| issn | 1561-8633 1684-9981 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Natural Hazards and Earth System Sciences |
| spelling | doaj-art-0f2c2531ce7a4ecaa21cfb0efa5eeb3b2025-08-22T09:09:14ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812025-08-01252803282210.5194/nhess-25-2803-2025Investigation of an extreme rainfall event during 8–12 December 2018 over central Vietnam – Part 2: An evaluation of predictability using a time-lagged cloud-resolving ensemble systemC.-C. Wang0D. V. Nguyen1D. V. Nguyen2T. V. Vu3P. Thi Thanh Nga4P.-Y. Chuang5K. B. Truong6Department of Earth Sciences, National Taiwan Normal University, Taipei, TaiwanDepartment of Earth Sciences, National Taiwan Normal University, Taipei, TaiwanViet Nam Institute of Meteorology, Hydrology and Climate Change, Hanoi, VietnamViet Nam Institute of Meteorology, Hydrology and Climate Change, Hanoi, VietnamViet Nam Institute of Meteorology, Hydrology and Climate Change, Hanoi, VietnamDepartment of Earth Sciences, National Taiwan Normal University, Taipei, TaiwanViet Nam Institute of Meteorology, Hydrology and Climate Change, Hanoi, Vietnam<p>This is the second part of a two-part study that investigates an extreme rainfall event that occurred from 8 to 12 December 2018 over central Vietnam (referred to as the D18 event). In this part, the study aims to evaluate the practical predictability of the D18 event using the quantitative precipitation forecasts (QPFs) from a time-lagged cloud-resolving ensemble system. To do this, 29 time-lagged (8 d in forecast range) high-resolution (2.5 km) members were run, with the first member initialized at 12:00 UTC on 3 December and the last one at 12:00 UTC on 10 December 2018. Between the first and the last members are multiple members that were executed every 6 h. The evaluation results reveal that the cloud-resolving model (CReSS) predicted the rainfall fields in the short range (less than 3 d) well for 10 December (the rainiest day). Particularly, the CReSS model shows high skill in heavy-rainfall QPFs for this date with a similarity skill score (SSS) greater than 0.5 for both the last five members and the last nine members. The good results are due to the model having good predictions of relevant meteorological variables such as surface winds. However, the predictive skill is reduced at lead times longer than 3 d, and it is challenging to achieve good QPFs for rainfall thresholds greater than 100 mm at lead times longer than 6 d. These results also confirmed our scientific hypothesis that the cloud-resolving time-lagged ensemble system (using the CReSS model) improved the QPFs of this event in the short range. Furthermore, the results also demonstrated that a decent QPF can be made at a longer lead time (by a member initialized at 18:00 UTC on 4 December).</p> <p>In addition, the ensemble-based sensitivity analysis (ESA) of 24 h rainfall in central Vietnam shows that it is highly sensitive to initial conditions, not only at lower levels but also at upper levels. The rainfall is sensitive to both kinematics and moisture convergence at low levels, and such sensitivities decrease with increasing lead time. The ESA also facilitates a better understanding of the mechanisms in the D18 event, implying that it is meaningful to apply ESA to control initial conditions in the future.</p>https://nhess.copernicus.org/articles/25/2803/2025/nhess-25-2803-2025.pdf |
| spellingShingle | C.-C. Wang D. V. Nguyen D. V. Nguyen T. V. Vu P. Thi Thanh Nga P.-Y. Chuang K. B. Truong Investigation of an extreme rainfall event during 8–12 December 2018 over central Vietnam – Part 2: An evaluation of predictability using a time-lagged cloud-resolving ensemble system Natural Hazards and Earth System Sciences |
| title | Investigation of an extreme rainfall event during 8–12 December 2018 over central Vietnam – Part 2: An evaluation of predictability using a time-lagged cloud-resolving ensemble system |
| title_full | Investigation of an extreme rainfall event during 8–12 December 2018 over central Vietnam – Part 2: An evaluation of predictability using a time-lagged cloud-resolving ensemble system |
| title_fullStr | Investigation of an extreme rainfall event during 8–12 December 2018 over central Vietnam – Part 2: An evaluation of predictability using a time-lagged cloud-resolving ensemble system |
| title_full_unstemmed | Investigation of an extreme rainfall event during 8–12 December 2018 over central Vietnam – Part 2: An evaluation of predictability using a time-lagged cloud-resolving ensemble system |
| title_short | Investigation of an extreme rainfall event during 8–12 December 2018 over central Vietnam – Part 2: An evaluation of predictability using a time-lagged cloud-resolving ensemble system |
| title_sort | investigation of an extreme rainfall event during 8 12 december 2018 over central vietnam part 2 an evaluation of predictability using a time lagged cloud resolving ensemble system |
| url | https://nhess.copernicus.org/articles/25/2803/2025/nhess-25-2803-2025.pdf |
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