Marine & Environmental Sciences Faculty Articles

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Publication Title

Journal of Advances in Modeling Earth Systems


Climate Process Team, NOAA Climate Forecast System, Madden-Julian Oscillation, DYNAMO field campaign, Ocean mixing process





First Page



Given the increasing attention in forecasting weather and climate on the subseasonal time scale in recent years, National Oceanic and Atmospheric Administration (NOAA) announced to support Climate Process Teams (CPTs) which aim to improve the Madden-Julian Oscillation (MJO) prediction by NOAA’s global forecasting models. Our team supported by this CPT program focuses primarily on the improvement of upper ocean mixing parameterization and air-sea fluxes in the NOAA Climate Forecast System (CFS). Major improvement includes the increase of the vertical resolution in the upper ocean and the implementation of General Ocean Turbulence Model (GOTM) in CFS. In addition to existing mixing schemes in GOTM, a newly developed scheme based on observations in the tropical ocean, with further modifications, has been included. A better performance of ocean component is demonstrated through one-dimensional ocean model and ocean general circulation model simulations validated by the comparison with in-situ observations. These include a large SST diurnal cycle during the MJO suppressed phase, intraseasonal SST variations associated with the MJO, ocean response to atmospheric cold pools, and deep cycle turbulence. Impact of the high-vertical resolution of ocean component on CFS simulation of MJO-associated ocean temperature variations is evident. Also, the magnitude of SST changes caused by high-resolution ocean component is sufficient to influence the skill of MJO prediction by CFS.

Plain Language Summary

The idea of Climate Process Teams (CPTs) has been suggested in early 2000 to accelerate the development of numerical models for prediction of weather and climate. Members of CPTs consist of observationalists, theoreticians, process-oriented modelers, and scientists at modeling centers, and thus knowledge obtained from observational and process-oriented researches can be transferred to the improvement of physical process representations in global climate models. The CPT program initiated by NOAA in 2015 specifically aims to improve prediction of Madden-Julian Oscillation (MJO) which is the major intraseasonal (30-90 day) fluctuation in the tropical atmosphere. Our CPT primarily focuses on improving the representation of upper ocean processes relevant to the MJO in NOAA’s operational climate prediction system: Climate Forecast System (CFS). Performance of the improved ocean component of CFS is evaluated through a comparison of model simulations with high-quality in-situ data collected during the recent field campaign which was designed to monitor ocean and atmospheric variability associated with the MJO. The improvement includes the realistic model simulation of large upper ocean warming during daytime through implementing high vertical resolution mixing schemes near the surface. The results demonstrate a significant impact of the high-vertical resolution ocean component in CFS on the MJO prediction skill.


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Additional Comments

This research is supported by NOAA Grant NA15OAR431074. Computing resources were provided partly by the HPC systems at the Texas A&M University (College Station and Corpus Christi)and the Climate Simulation Laboratory at NCAR’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation. TS and SP are supported by DOD grant W911NF-20-1-0309. TS is also supported by NSF grant OCE-1658218 and NOAA grant NA17OAR4310255.Constructive comments by two anonymous reviewers are gratefully acknowledged.





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