Xian Wu (吴贤）
Ph.D. candidate in Climate Dynamics
Institute for Geophysics, Jackson School of Geosciences
The University of Texas at Austin
Ph.D. Research
Duration of El Niño and La Niña: Mechanisms and Predictability
[Composite sea surface temperature anomalies (°C, shading interval at 0.2) during the mature phase of (left) warming phase (El Niño) and (right) cooling phase (La Niña) of El Niño–Southern Oscillation events during 1900-2018]
El Niño-Southern Oscillation (ENSO) causes episodic warming (El Niño) and cooling (La Niña) of the tropical Pacific and affects global weather patterns via atmospheric teleconnections. ENSO events that last multiple years would prolong and exacerbate their climate impacts. It is therefore critical to understand the dynamics controlling the event duration and predict these long-lasting events with sufficient lead times. Here are my three projects are in progress:
1. Dynamics of ENSO event duration
Oceanic and atmospheric processes that affect the duration of El Niño and La Niña are investigated based on both observational data and a long control simulation of the Community Earth System Model version 1 (CESM1). The duration of El Niño is strongly affected by the timing of its onset, while the duration of La Niña largely depends on the preceding event amplitude.
See more in Wu, X., Y. M. Okumura, and P. N. DiNezio, 2019: What Controls the Duration of El Niño and La Niña Events? J. Climate, 32, 5941–5965, https://doi.org/10.1175/JCLI-D-18-0681.1.
El Niño events that develop early in the calendar year tend to terminate after the first peak, while those develop later usually last for a second year. La Niña events preceded by strong El Niño events tend to last two years. (Figure adapted from Wu et al. 2019).
2. Perfect model forecasts of El Niño duration
To investigate the potential predictability of El Niño duration based on the onset timing, I conducted a suite of perfect model forecasts using the CESM1 (i.e., use CESM1 to predict itself). The CESM1 successfully predict the termination of April-onset El Niño but the continuation of September-onset El Niño.
Wu, X., Y. M. Okumura, and P. N. DiNezio, 2021: Predictability of El Niño Duration Based on the Onset Timing. J. Climate. 34, 1351–1366, https://doi.org/10.1175/JCLI-D-19-0963.1.
For El Niño events that onset in April and September selected from the CESM control simulation, 30-member ensemble forecasts are generated by initializing the CESM1 with the same oceanic conditions in the onset month and perturbed atmospheric conditions.
3. Predictability of El Niño and La Niña duration in the real world
To explore the long-term predictability of ENSO event duration in the real world, we analyze a suite of ensemble seasonal forecasts conducted with the Community Earth System Model, version 1 (CESM1). Three sets of ensemble forecasts are initialized with observed oceanic conditions on every March, June, and November 1st during 1954-2015 and consist of 20-40 ensemble members with slightly different atmospheric initial conditions. All forecasts are integrated at least for two years. Preliminary analysis shows that the CESM1 has high skills of predicting the duration of El Niño and La Niña with lead times ranging from 6 to 24 months.
Wu, X., Y. M. Okumura, C. Deser, and P. N. DiNezio, 2021: Two-year Dynamical Predictions of ENSO Event Duration during 1954–2015. J. Climate. 34, 4069–4087, https://doi.org/10.1175/jcli-d-20-0619.1.
Collaborative Research:
Response of tropical hydroclimate during abrupt climate change
Paleoclimate data show patterns of global temperature and hydroclimate changes during intervals when the North Atlantic cools, particularly during the most recent Heinrich Stadial 1 (HS1; 17-15 ka). We combine ~200 paleoclimate data records and 15 model simulations to investigate oceanic and atmospheric processes responsible for the tropical rainfall changes during the HS1.
Current Research
Decadal Predictability and Prediction Skill in the Pacific Ocean
Coming soon....