Research Projects
My research interests are centered around high resolution climate modeling, mesoscale convective systems, and model/data comparison.
Equilibrium Climate Sensitivity Across Cenozoic Warm Intervals
Equilibrium climate sensitivity (ECS) quantifies the amount of warming resulting from a doubling of the atmospheric CO2 forcing. Despite recent advancements in climate simulation capabilities and global observations, there remains large uncertainty on the degree of future warming. To help alleviate this uncertainty, past climates provide a valuable insight into how the Earth will respond to elevated atmospheric CO2. However, there is evidence to suggest that ECS is dependent on background climate warmth, which may interfere with the direct utilization of paleo-ECS to understand present-day ECS. Thus, it is important that a range of different climate states are considered to better understand the factors modulating the relationship between CO2 and temperature. In this study, we focus on three time intervals: the mid-Pliocene Warm Period (3.3 – 3.0 Ma), the mid-Miocene (20 – 11.6 Ma), and the early Eocene (~50 Ma), in order to sample ECS from Cenozoic coolhouse to hothouse climates (see image above). Here, we combine a linear framework of constraining the ECS and its uncertainty with several published methods to estimate the global mean surface temperature (GMST) from sparse proxy records. This framework utilizes an emergent constraint between the simulated GMST changes and climate sensitivities across the model ensemble. For each time interval, we employ a combination of parametric and non-parametric functions, coupled with a probabilistic approach to derive a refined estimate. Preliminary results for the Pliocene indicate a GMST reconstruction of approximately 19.3°C, which is higher than previous estimates that were derived using only marine records. Using this estimate, we calculate an ECS that is also higher than previously published values, especially due to the inclusion of high-latitude terrestrial temperature records into our estimates. Intriguingly, using the consistent methodology, our calculated ECS for the early Eocene is lower than that of the mid-Pliocene. This result does not support an amplified ECS in hothouse climate, and points to a potentially important role of ice albedo feedback in amplifying the ECS in coolhouse climate. Ongoing work will apply the same methodology to the mid-Miocene and further investigate the source for the estimated ECS state dependency between these climate intervals.
Tracking Mesoscale Convective Systems
Example of a mesoscale convective system developing over Nebraska (https://cimss.ssec.wisc.edu/satellite-blog/archives/673)
High-resolution climate models are essential for resolving finer-scale weather systems, which are among the most impactful effects of climate change. However, the study of mesoscale convective systems (MCSs) throughout Earth's history has been limited by computational constraints. This project aims to track MCSs across multiple paleoclimate intervals using a series of fully coupled high-resolution (HR) climate simulations, including the mid-Holocene, Last Glacial Maximum (LGM), mid-Pliocene Warm Period (mPWP), and Early Eocene Climatic Optimum (EECO). These simulations are run using the water isotope-enabled version of CESM1.3 with an atmospheric and land resolution of ~0.25° and an ocean and sea ice resolution of 0.1°, enabling the presence of organized mesoscale systems and an eddy-resolving ocean component.​ This study will investigate the dynamics governing MCS characteristics and assess whether changes in storm statistics scale with global mean temperature, similar to extreme precipitation patterns. By examining the characteristics and dynamics of MCSs in these different climate states, we aim to uncover patterns and relationships between storm statistics and global mean temperature. This research will provide valuable insights into past hydroclimate changes and inform predictions of future MCS behavior in a warming world.
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This work began with the development of a new MCS tracking algorithm using a deep learning model, which was done in collaboration with Dr. Maria J. Molina at the University of Maryland. This model was used in a new MCS tracking intercomparison effort (MCSMIP; submitted to JGR Atmospheres) and is now being applied to a suite of high-resolution paleoclimate simulations.
Mid-Pliocene North American Monsoon
The North American Monsoon (NAM) delivers approximately 70% of the average annual precipitation to northwestern Mexico and about 40-50% to the southwestern USA. Previous research has shown that NAM precipitation will weaken in response to elevated levels of atmospheric CO2 in future as a result of sea surface warming and changing sea surface temperature (SST) pattern. However, when analyzing paleoclimate reconstructions for the mid-Pliocene (3.0 – 3.3 Ma), the closest CO2-driven warm climate analog to today, various records suggest a wetter NAM region and enhanced summer precipitation. In contrast, state-of-the-art atmosphere-ocean coupled models typically simulate year-round precipitation reduction during this interval. However, in our high-resolutionsimulation with 25 km resolution of atmosphere and land and 100 km of ocean and sea ice, we discovered that summer precipitation did not weaken and even enhanced over the Sierra Madre Occidental (SMO) and Gulf of Mexico despite lowered mid-Pliocene surface elevation over the SMO, which tends to reduce the NAM precipitation. By adapting a feature tracking algorithm (TempestExtremes) to detect mesoscale convective systems (MCSs), we revealed an increase of summertime MCS frequency and MCS-incurred precipitation in the NAM region in our mid-Pliocene simulation, which accounts for the majority of modeled increase in high-resolution summer precipitation. These MCS changes are attributable to an enhanced daily peak of convective available potential energy and surface sensible heat flux corresponding to the greening of the land surface. Our results highlight the importance of changing weather system and land surface in modulating the hydroclimate condition in the NAM region. Both are rarely explored in current climate projections.
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This project is completed and has been submitted to Science Advances!
Results from simulations using the Community Earth System Model showing wetter conditions during the Pliocene on the Eastern side of the Sierra Madre Occidental mountains in the high resolution simulations (right)
See more of this work here:
Greenville County, SC, Farmland Conservation (Undergraduate Thesis Project)
This work was recently published in the Journal of Land Use Science! Check out our article here.
Scroll through below to see an overview of my research as an undergraduate at Furman University