Effects of Semistochastic Westerly Wind Bursts on ENSO Predictability. Issue 14 (24th July 2020)

• Record Type: Journal Article
• Authors: Tan, Xiaoxiao; Tang, Youmin; Lian, Tao; Zhang, Shouwen; Liu, Ting; Chen, Dake
• Is Part Of: Geophysical research letters. Volume 47:Issue 14(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-07-24
• Subjects: WWBs -- parameterization -- ENSO prediction -- central Pacific El Niño -- eastern Pacific El Niño; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2019GL086828
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: Westerly wind bursts (WWBs) occurring over the tropical Pacific play an important role on El Niño‐Southern Oscillation (ENSO) dynamics. Currently, climate models have significant biases in their representation of WWBs, which may limit their ability to predict ENSO. In this study, we explore the possibility of improving ENSO prediction by introducing a semistochastic WWBs parameterization scheme into the Community Earth System Model (CESM). Three ensemble hindcasts, namely, the control run with the original CESM, the WWB run with parameterized WWBs, and the Non_WWB run with built‐in WWBs removed, are conducted for the period 1982–2016. We find that CESM with parameterized WWBs enables better ENSO prediction, especially for both amplitude and spatial distribution of eastern Pacific and central Pacific El Niño events. This improvement is related to more realistic representation of WWBs which leads to better prediction of surface wind stress anomalies and thermocline depth anomalies. Plain Language Summary: El Niño‐Southern Oscillation (ENSO) is the dominate climate phenomenon on Earth, with strong impacts on weather and climate across the globe; however, it is still difficult to predict this phenomenon accurately. Westerly wind bursts (WWBs) in the tropical Pacific play a key role during ENSO development, and their misrepresentation in climate models can limit the accuracy of ENSO prediction. Thus, improving the representation of WWBs in these models is a must. In this work, we improve the representation of WWBs in a climate model by adding a WWBs parameterization scheme and further investigate its effects on ENSO prediction. We find that this approach allows improving ENSO prediction significantly, especially for both the amplitude and spatial distribution of the warm El Niño phase. These encouraging results provide practical importance for ENSO prediction. Key Points: Parameterized WWBs can improve ENSO prediction, especially for El Niño The distribution and strength of eastern Pacific El Niño and central Pacific El Niño are both predicted more accurately More realistic reproduction of surface wind anomalies is, potentially, the key factor for improving prediction