Preprints
https://doi.org/10.5194/nhess-2023-192
https://doi.org/10.5194/nhess-2023-192
11 Dec 2023
 | 11 Dec 2023
Status: this preprint is currently under review for the journal NHESS.

Investigation of an extreme rainfall event during 8–12 December 2018 over central Viet Nam – Part 2: An evaluation of predictability using a time-lagged cloud-resolving ensemble system

Chung-Chieh Wang, Duc Van Nguyen, Thang Van Vu, Pham Thi Thanh Nga, Pi-Yu Chuang, and Kien Ba Truong

Abstract. 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 Viet Nam (referred to as the D18 event). In this part, the study aims to evaluate the predictability of the D18 event using a time-lagged cloud-resolving ensemble and a quantitative precipitation forecast system. To do this study, 29 time-lagged (8 days in lead time) high resolution (2.5 km) members were run, with the first members run at 12:00 UTC 3 December 2018, and the last member-run at 12:00 UTC 10 December 2018. Between the first and the last members are multiple members that run every 6-h. The evaluated results reveal that CReSS well predict the rainfall fields at the short-range forecast (less than 3 days) for 10 December (rainiest day). Particularly, results show CReSS has high skills in heavy-rainfall QPFs for the 24-h rainfall of 10 Dec with the SSS scores greater than 0.5 for both the last five members and the last nine members. These good results are due to the model having good predicts of other meteorological variables, such as surface wind fields. However, these prediction skills are reducing at extending lead time (longer than 3 days), and it is challenging to achieve the prediction of QPF for rainfall thresholds greater than 100 mm with lead time longer than 6 days. Besides, the ensemble sensitivity analysis of 24-hour rainfall responds to the initial conditions shows that the 24-hour rainfall is very sensitive with initial conditions, not only at the lower level but also at the upper level. The ensemble-based sensitivity is decreased with the increasing lead time. Through the analysis of thermodynamic and moisture sensitivities, it showed that the features of ESA facilitated a better understanding of the sensitivity of a precipitation forecast to the initial conditions, implying that it is meaningful to apply ESA to control initial conditions by work in the future.

Chung-Chieh Wang, Duc Van Nguyen, Thang Van Vu, Pham Thi Thanh Nga, Pi-Yu Chuang, and Kien Ba Truong

Status: open (until 17 Mar 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2023-192', Anonymous Referee #1, 23 Jan 2024 reply
Chung-Chieh Wang, Duc Van Nguyen, Thang Van Vu, Pham Thi Thanh Nga, Pi-Yu Chuang, and Kien Ba Truong
Chung-Chieh Wang, Duc Van Nguyen, Thang Van Vu, Pham Thi Thanh Nga, Pi-Yu Chuang, and Kien Ba Truong

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Short summary
CReSS well predict the rainfall fields at the short-range forecast (less than 3 days) for 10 December. These good results are due to the model having good predicts of other meteorological variables, such as surface wind fields. These prediction skills are reducing at lead time longer than 3 days. The 24-hour rainfall is very sensitive with initial conditions, not only at the lower level but also at the upper level. The ensemble-based sensitivity is decreased with the increasing lead time.
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