Monitoring and prediction of the Indian Ocean Dipole

Abstract: The National Meteorological and Hydrological Centers use diagnostic products to operationally monitor the Indian Ocean Dipole (IOD) and issue early warnings on impending extreme climate conditions, e.g. drought. However, such products require decision-making on the part of the service producer, including choosing an appropriate observational or model dataset for the product, a diagnostic that is a good representative of the phenomena, the baseline climatological period, or defining a criterion that needs to be met to identify an IOD event. These choices are sometimes subjective and the scientific rationale behind these subjective choices is often not properly documented. In this paper, we stock-take the current criteria used by multiple operational centers for the monitoring and prediction of the IOD. We find the widely-used Dipole Mode Index (DMI) is sensitive to the choice of SST dataset and time averaging (monthly vs 3-monthly mean DMI) and can lead to marked differences between centers on the current and future state of the IOD. Some regions in Southeast Asia, e.g. the southern Maritime Continent can experience the impact of the IOD on rainfall even when the IOD has not met the current operational threshold for an event. While most models are skillful in capturing the active phase of the IOD, all models have an overactive IOD strength. Calibration of DMI-based monitoring products is therefore recommended for the most skilful and reliable IOD predictions. All models also have low skill for forecasts initialized during January-May, although the skill is sensitive to verifying observations, and using a multi-observational mean dataset can yield better skill scores. Finally, we introduce an objective decision support system to assist climate forecasters in monitoring and predicting of IOD events and issuing timely alerts.

Biography: I am a Lecturer in Meteorological Risks at Institute for Risk and Disaster Reduction, University College London. My current research focuses on weather and climate extremes, with a particular emphasis on hydrometeorological extremes across Asia. I have several years of experience working in operational research, where I led and contributed to the development and delivery of climate services tailored to the users’ needs.