Quantifying the impact of SST feedback frequency on Madden–Julian oscillation simulations
-
Published:2024-05-15
Issue:9
Volume:17
Page:3897-3918
-
ISSN:1991-9603
-
Container-title:Geoscientific Model Development
-
language:en
-
Short-container-title:Geosci. Model Dev.
Author:
Lan Yung-Yao, Hsu Huang-Hsiung, Tseng Wan-LingORCID
Abstract
Abstract. This study uses the Community Atmosphere Model 5.3 coupled to a 1-D ocean model to investigate the effects of intraseasonal sea surface temperature (SST) feedback frequency on Madden–Julian oscillation (MJO) simulations with intervals at 30 min and 1, 3, 6, 12, 18, 24, and 30 d. The large-scale nature of the MJO in simulations remains intact with decreasing feedback frequency, although it becomes increasingly unrealistic in both structure and amplitude, until 1 per 30 d when the intraseasonal fluctuations are overwhelmingly dominated by unorganized small-scale perturbations in both atmosphere and ocean, as well as at the atmosphere–ocean interface where heat and energy are rigorously exchanged. The main conclusion is that the less frequent the SST feedback, the more unrealistic the simulations. Our results suggest that more spontaneous atmosphere–ocean interaction (e.g., ocean response once every time step to every 3 d in this study) with high vertical resolution in the ocean model is a key to the realistic simulation of the MJO and should be properly implemented in climate models.
Funder
Ministry of Science and Technology, Taiwan Academia Sinica
Publisher
Copernicus GmbH
Reference68 articles.
1. Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P. P., Janowiak, J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J., Arkin, P., and Nelkini, E.: The Version 2.1 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis (1979–Present), J. Hydrometeor., 4, 1147–1167, https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2, 2003. 2. Amante, C. and Eakins, B. W.: ETOPO1 1 arc-minute globe relief model: Procedures, data sources and analysis, NOAA Tech. Memo. NESDIS NGDC-24, NOAA, Silver Spring, MD, 19 pp., https://doi.org/10.7289/V5C8276M, 2009. 3. Banzon, V. F., Reynolds, R. W., Stokes, D., and Xue, Y.: A 1/4-spatial-resolution daily sea surface temperature climatology based on a blended satellite and in situ analysis, J. Climate, 27, 8221–8228, https://doi.org/10.1175/JCLI-D-14-00293.1, 2014. 4. Behringer, D. W. and Xue, Y.: Evaluation of the global ocean data assimilation system at NCEP: The Pacific Ocean, Eighth Symposium on Integrated Observing and Assimilation Systems for Atmosphere, Oceans, and Land Surface, AMS 84th Annual Meeting, Washington State Convention and Trade Center, Seattle, Washington, 11–15 January 2004, https://ams.confex.com/ams/pdfpapers/70720.pdf (last access: 8 May 2024), 2004. 5. Chang, M.-Y., Li, T., Lin, P.-L., and Chang, T.-H.: Forecasts of MJO Events during DYNAMO with a Coupled Atmosphere-Ocean Model: Sensitivity to Cumulus Parameterization Scheme, J. Meteorol. Res., 33, 1016–1030, https://doi.org/10.1007/s13351-019-9062-5, 2019.
|
|