Lead supervisor: Michael Herzog, Geography
Co-supervisor: Ali Mashayek, Earth Sciences
Brief summary:
The project will quantify and analyse biases and uncertainties of climate models in their representation of the El Niño–Southern Oscillation (ENSO).
Importance of the area of research concerned:
El Niño–Southern Oscillation (ENSO) is one of the most important interannual fluctuations of the climate system. ENSO affects many parts of the globe through teleconnections and influences Pacific marine ecosystems and commercial fisheries. Hence, ENSO predictability and future changes in ENSO intensity and frequency are of considerable interest. Changes in the ENSO climatology under climate change can only be assessed with climate models. However, future
changes of El Niño in climate models are model dependent (Guilyardi et al., 2012). Reasons for this are poorly understood.
Project summary :
The goal of the project is an improved understanding of the triggering and evolution of ENSO events. The identification and study of important processes will help to identify the best performing climate model and enable a better representation of ENSO in climate models.
Continuing and expanding previous work by Lai et al. (2015) and Lai et al. (2018) this project will investigate important processes for the evolution of ENSO and their representation in climate models. Processes identified in the real atmosphere ocean system will be compared to their representation in climate models. Underlying mechanisms will tested in additional climate model simulations.
What will the student do?:
In the first instance, the model for ENSO predictions developed by Lai et al. (2018) for the observed ENSO events of the last forty years will be applied to existing data from climate models that is representative for the climate of the 20th century. Biases in the mean ocean state, for example, will be identified and used to modify the original prediction model for a best fit to a particular climate model. Climate models will be selected from the CMIP6 archive or from more recent high resolution global atmosphere ocean simulations.
In a second step, atmospheric conditions that trigger El Nino events will be identified in observations and compared to their counterparts in climate models.
Finally, additional simulations with the NCAR Community Earth System Model CESM2 climate model will be performed to test hypotheses and mechanisms developed during the first two parts of the project.
References - references should provide further reading about the project:
Lai, ., Herzog, M. and Graf, H.F., 2018. ENSO forecasts near the spring predictability barrier and possible reasons for the recently reduced predictability. Journal of Climate, v. 31, p. 815-838.
Lai, A.W.-.C., Herzog, M. and Graf, H.-.F., 2015. Two key parameters for the El Niño continuum: Zonal wind anomalies and Western Pacific subsurface potential temperature. Climate Dynamics, v. 45, p.3461-3480.
Guilyardi, E., H. Bellenger, M. Collins, S. Ferrett, W. Cai, and A. Wittenberg, 2012. A first look at ENSO in CMIP5. CLIVAR Exchanges, 58, 29-32.
Applying
You can find out about applying for this project on the Department of Geography page.