I am Danni Du (杜旦尼), a fifth-year Ph.D. student in the Department of Atmospheric and Oceanic Sciences at University of Colorado Boulder. My Ph.D. advisors are Dr. Aneesh Subramanian and Dr. Weiqing Han. The main focus of my research work is to improve the prediction skill and understand the predictability in the tropics at subseasonal time scales. I am particularly interested in the Madden-Julian Oscillation (MJO) and the Indian Summer Monsoon (ISM), and the role that air-sea interaction plays in these phenomena.

Email

danni.du@colorado.edu

A summary of my Ph.D. work

Assessing the impact of the ocean data assimilation on MJO predictions in coupled subseasonal forecast models

Though the atmospheric biases might hinder the contribution from the improved ocean initialization to the MJO prediction, a better initialization of the ocean stratification can lead to better forecasted ocean mixing and air-sea interactions, and thus more realistic MJO propagation across the Maritime Continent.

Investigating the MJO predictability change under global warming using an information theory technique

By using the Weighted Permutation Entropy method, we find an increase in the MJO predictability under global warming. The MJO oscillation patterns and the eastward propagation pattern are getting more regular in a warming climate, and thus lead to the increasing predictability. The increase in the MJO predictability is an opportunity for future Subseasonal-to-seasonal predictions.

Identifying the drivers of the ISM subseasonal anomalies using a causal discovery method

Causal analysis discovers that the pressure anomalies over the tropical Western Pacific can modulate the ISM subseasonal anomalies via westward propagating Rossby Waves. This causal effect has enhanced over the recent decades, as more Rossby waves can emanate over the tropical Western Pacific due to the higher mean SST and the Warm Pool expansion.