Interests
climate change, climate variability, sea ice, ocean general circulation, and ice-ocean-atmosphere interactions
Current Projects
Ocean circulation under various climate states
Environmental Science and Engineering, California Institute of Technology
Advisors: Andrew Thompson, Emily Newsom, and Jess Adkins
Understanding how ocean circulation responds to climatic changes is important for interpreting past behavior and predicting future changes. In particular, it is crucial to connect large-scale processes, such as inter-basin heat exchange and global ocean overturning, with more regional processes, such as water mass transformation and air-sea exchange, to fully grasp how the general circulation of the ocean responds to change. Here, we are using a fully-coupled climate model that was forced with a range of greenhouse-gas concentrations and different orbital configurations to study the structure of ocean circulation after experiencing large climatic changes.
Projections of Arctic sea ice
Environmental Science and Engineering, California Institute of Technology
Advisors: Tapio Schneider and Robert Wills
Given that accurate projections of Arctic sea ice are a crucial commodity for a broad range of stakeholders, quantifying the sources of uncertainty in these projections is a necessary step to reduce uncertainty. In particular, it is important to disentangle the components of Arctic sea ice loss that are natural and the components that are forced by humans, and furthermore understand why climate models have different responses to increasing greenhouse-gas concentrations. Using an ensemble of fully-coupled global climate models that represent different model physics and different realizations of natural variability, we are studying the physical processes that govern the evolution of Arctic sea ice, with a particular focus on processes that cause spread across climate model projections.
Previous Projects
Influence of the Pacific Ocean on Arctic sea ice
Department of Atmospheric Sciences, University of Washington
Advisor: Ed Blanchard-Wrigglesworth
Areas of persistent sea-surface temperature variations can force persistent circulation anomalies in the atmosphere. This preferred circulation response allows remote climatic events in one area of the globe to influence regional climate elsewhere. Our understanding of these remote connections, however, is derived from the temporally-limited observational record, which means we are only seeing a glimpse of these patterns. A characterization of their stationarity spanning decades and centuries is needed to improve seasonal-to-interannual-to-decadal climate predictions. This necessitates the use of alternative approaches to study these relationships. Using an ensemble of fully-coupled global climate models, we studied how a relationship between the Pacific Ocean and Arctic sea ice evolves in time and showed that this relationship is non-stationary in time. In the context of observed Arctic sea ice, when this mode shifts in the future, we can expect significant changes to sea ice loss (see Bonan and Blanchard-Wrigglesworth, 2020).
Response of the hydrologic cycle to global warming
Department of Atmospheric Sciences, University of Washington
Advisors: Kyle Armour, Gerard Roe, and Nick Siler
Idealized models allow us to better understand the behavior of comprehensive global climate models. Recent studies have shown that a simple model that makes an assumption about how atmospheric heat transport behaves is remarkably successful at emulating the response of climate models to an increase of CO2. Through the lens of this simple model, we characterized the spread in the predicted patterns of evaporation and precipitation made by climate models under global warming.
Regional predictions of Arctic sea ice
Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA)
Advisors: Mitch Bushuk and Mike Winton
Accurately predicting Arctic sea ice is of interest to many stakeholders, including indigenous communities, fisheries, and the shipping industry. Much progress has been made with predicting pan-Arctic sea-ice extent, but considerable work still remains to accurately predict regional Arctic sea-ice extent — which often has more societal relevance. Using an ensemble of fully-coupled global climate models and a simple linear regression model, we demonstrated that there is a robust springtime predictability barrier across dynamical models, which suggests there is a fundamental limit on accurate forecasts of regional Arctic sea ice and a physical mechanism universal to all global climate models (see Bonan et al., 2019).
Glacier trends and natural variability in the climate system
Department of Earth and Space Sciences, University of Washington
Advisors: Knut Christianson and John Christian
Glacier retreat is an iconic symbol of climate change. Mass loss from any particular glacier, however, is the result of both anthropogenic and natural changes. Because of this, attributing observed glacier retreat to anthropogenic warming is difficult and regional studies are needed in order quantify the role of natural variability on the observed trends. The North Atlantic region is a perfect case study to assess the role of natural climate variability on glacier retreat as there are high quality mass-balance records that reside in regions of large climate variability. Using a statistical method known as dynamical adjustment, we studied how circulation anomalies affect seasonal glacier mass-balance trends to quantify the influence of natural variability on glacier mass loss in the North Atlantic (see Bonan et al., 2019).
Uncertainty in the spatial pattern of warming
Department of Atmospheric Sciences, University of Washington
Advisors: Kyle Armour, Gerard Roe, Nick Siler, and Nicole Feldl
As global climate models have increased in complexity, the number of physical processes representing the climate system has also increased. A central goal of climate science is to understand how uncertainty in these physical processes translates into uncertainty in the forced response. Within climate models, though, it is a challenge to disaggregate the individual factors contributing to uncertainty and explore each in a systematic way. To circumvent this problem, we used a simple model — which describes how energy is transported from the tropics to the poles — to study uncertainty in the spatial pattern of warming (see Bonan et al., 2018 and this EOS spotlight).
Effects of orography on large-scale atmospheric and oceanic circulation
Department of Atmospheric Sciences, University of Washington
Advisors: Dargan Frierson and Rachel White
Mountains play an important role in shaping the Earth's climate. Not only do these features modulate the circulation of the atmosphere, but they also control the strength of circulation in the ocean through changes in precipitation and wind patterns. By running idealized experiments in which mountains were removed from specific geographic regions in global climate models, we studied the influence of orography on large-scale oceanic and the atmospheric circulation.