Researcher Spotlight - Meet Dr. Han Wang, Developing innovative tools

As a Young Project Leader in area W2 “Observed and Simulated Internal Tides: Generation, Modification by Eddies, and Contribution to Energy Budget”, Dr. Han Wang’s role is to develop machine learning algorithms to infer internal tidal energetics from satellite observations. Her other research interests include interactions between currents and surface waves inferred from satellite observations, and multi-scale dynamics inferred from surface drifter observations; she collaborates with researchers in areas L3, T2, W4, and M3 too.

What motivates you to work in this field?   

“I’m interested in understanding complex, turbulent systems, and the ocean is one of them. There are many unanswered questions in physical oceanography that are intriguing to explore. Not only are these questions fascinating, but they are also crucial for enhancing our understanding of climate processes, which has practical importance for predicting and managing climate change.” 

How has your background and career path shaped your approach to climate science? 

“During my graduate school, I was exposed to beautiful classical theories in geophysical fluid dynamics, as well as intriguing modern questions. This includes, for example, the Gage and Nastrom (1986) spectra observed in the atmosphere - some existing theories could explain part, but not all, of the behaviour of the spectra. My first research work during my graduate school was to develop some tool to help interpret the dynamical origins of this type of spectra. I enjoyed doing it, and I figured that I do love doing something theoretical/numerical and see how it corresponds to what can be observed in nature. This is the common motif for my other works that followed.  

My undergraduate and graduate educations were heavy in physics and applied mathematics. They make me feel comfortable with pencil-and-paper derivations and programming, which helps me adapt to different theoretical and numerical tools promptly to different research questions.” 

What are your primary research interests?  

“My main interest is in understanding ocean dynamics through analytical and data-driven methods, which can ultimately be applied to observational data. In area W2, I focus on internal tides and their energetics. They are important to the ocean because the way they are generated and modulated is crucial to the ocean's energy budget, the understanding of which can improve predictions of long-term, large-scale behaviour in climate models.” 

What do you believe are the most pressing challenges in climate science today, and how does your work contribute to addressing them?   

“One of the most pressing challenges is that climate models are still not perfect. One origin of the imperfection is that due to computational costs, small-scale processes cannot be completely resolved and must be parametrized. Results gained from my work can help us understand the relation between small-scale and large-scale processes in the ocean, which could help improving the representation of small scales in climate models.” 

How does collaboration across different institutions and disciplines enhance the impact of your research? 

“As my research centres around developing tools to understand better about ocean dynamics from limited observations, it really helps to communicate conveniently with the observationists, modellers and theoreticians at TRR 181. By talking to observationists, I become more aware what types of state-of-the-art observations are there, what their limitations are, and what type of information can help 

observationists design their next campaigns. By talking to modellers, I become more aware what types of processes are currently under-represented in models; I also sometimes ask modellers for their model outputs to use as a playground for some methods I develop. By talking to theoreticians, I become more aware what methods I could try for the problems I’m solving, and what steps I take may be too handwavy, 

These communications lead to ongoing collaborations I have with mathematicians in area M2 “Machine learning methods to handle flows with multiple scales”, observationists/theoreticians/modellers in area L3 “Energetics inferred from surface drifters”, theoreticians/modellers in area T2 “Impacts of currents on surface waves”, and modellers in area W4 “Machine learning for tidal mixing parametrization”.” 

What advice would you give to students or young researchers interested in pursuing a career in climate sciences? 

“For someone thinking about becoming a researcher in climate science: some aspects of the work conditions, such as moderate salaries for years, and having to move between places before finding a permanent job, do not justify doing what you 

would not enjoy. Therefore, it is important to make sure you’d enjoy doing the research. The work conditions are not bad if you get to do what you love doing.”    

What is the best way to connect with you for potential research collaboration?  

"You can shoot me an email at han.wang[at]uni-hamburg.de."