Preprints
https://doi.org/10.5194/gmd-2022-159
https://doi.org/10.5194/gmd-2022-159
Submitted as: model experiment description paper
04 Aug 2022
Submitted as: model experiment description paper | 04 Aug 2022
Status: this preprint is currently under review for the journal GMD.

Monthly-Scale Extended Predictions Using the Atmospheric Model Coupled with a Slab-Ocean

Zhenming Wang1,2, Shaoqing Zhang1,2,3, Yishuai Jin1,2, Yinglai Jia1, Yangyang Yu1,2, Yang Gao3,4, Xiaolin Yu1,2,3, Mingkui Li1,2,3, Xiaopei Lin1,2,3, and Lixin Wu1,2,3 Zhenming Wang et al.
  • 1Key Laboratory of Physical Oceanography, Ministry of Education, Institute for Advanced Ocean Study, Frontiers Science Center for Deep Ocean Multispheres and Earth System (DOMES), Ocean University of China, Qingdao, 266100, China
  • 2College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, 266100, China
  • 3Pilot National Laboratory for Marine Science and Technology, Qingdao, 266100, China
  • 4Key Laboratory of Marine Environment and Ecology, and Frontiers Science Center for Deep Ocean Multispheres and Earth System (FDOMES), Ministry of Education, Ocean University of China, Qingdao 266100, China

Abstract. Given the good persistence of sea surface temperature (SST) due to the slow-varying nature of the ocean, an atmospheric model coupled with a Slab Ocean Model (SOM) instead of a 3-D dynamical ocean model is designed as an efficient approach for extended-range predictions. The prediction experiments from July to December 2020 are performed based on the Weather Research and Forecasting (WRF) model coupled to the SOM (WRF-SOM) with the initial and boundary conditions same as the WRF coupled to the Regional Ocean Model System (WRF-ROMS). The WRF-SOM is verified to have better performance of SSTs in the extended-range predictions than WRF-ROMS since it avoids the complicated model biases from the ocean dynamics and seabed topography when extended-range predictions are made using a 3-D dynamical ocean model. The improvement of SSTs can lead to the remarkable impact on the response of the atmosphere from the surface to the upper layer. Taking typhoon as an example of extreme events, the WRF-SOM can obtain comparable intensity predictions and slightly improved track predictions due to the improved SSTs in the initialized WRF-SOM system. Overall, the WRF-SOM can ensure the stability of extended-range prediction and reduce the demand for computing resources by roughly 50 %.

Zhenming Wang et al.

Status: open (until 29 Sep 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Zhenming Wang et al.

Zhenming Wang et al.

Viewed

Total article views: 105 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
89 12 4 105 1 1
  • HTML: 89
  • PDF: 12
  • XML: 4
  • Total: 105
  • BibTeX: 1
  • EndNote: 1
Views and downloads (calculated since 04 Aug 2022)
Cumulative views and downloads (calculated since 04 Aug 2022)

Viewed (geographical distribution)

Total article views: 92 (including HTML, PDF, and XML) Thereof 92 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 08 Aug 2022
Download
Short summary
To improve the numerical model predictability of monthly extended-range scales, we use the simplified SOM to restrict the complicated SST bias from 3-D dynamical ocean model. As for SST prediction, whether in space or time, the WRF-SOM is verified to have the performance than that of the WRF-ROMS, which has a significant impact on the atmosphere. For the extreme weather event such as typhoons, the predictions of WRF-SOM are in good agreement with WRF-ROMS.