Event Detail

Event Type: 
Applied Mathematics and Computation Seminar
Date/Time: 
Friday, February 25, 2022 - 12:00 to 12:50
Location: 
ZOOM

Speaker Info

Institution: 
Woodwell Climate Research Center
Abstract: 

A significant portion of the Arctic coastal plain is classified as polygonal tundra and plays a vital role in soil carbon cycling. Recent research suggests that lateral transport of dissolved carbon could exceed vertical carbon releases to the atmosphere. However, the details of lateral subsurface flow in polygonal tundra have not been well studied. We incorporated a subsurface transport process into an existing state-of-art hydrothermal model. The model captures the physical effects of freeze/thaw cycles on lateral flow in polygonal tundra. The new modeling capability enables non-reactive tracer movement within subsurface. We utilized this new capability to investigate the impact of freeze/thaw cycle on lateral flow in the polygonal tundra. Our study indicates the important role of freeze/thaw cycle and freeze-up effect on lateral tracer transport, suggesting that dissolved species could be transported from the middle of the polygon to the sides within a couple of thaw seasons. Introducing lateral carbon transport in the climate models could substantially reduce the uncertainty associated with the impact of thawing permafrost.

BIO: Dr Jafarov is a computational climate and earth scientist, with a (2013) PHD from the Department of Geology and Geophysics at the University of Alaska Fairbanks on modeling permafrost and permafrost-related processes in Alaska. He worked at the Snow and Ice Data Center and Institue for Arctic and Alpine Research at the University of Colorado Boulder (2013-16) and at the Los Alamos National Laboratory (2016-2021) as a Staff Scientist. Currently he is working at the Woodwell Climate Research Center as a Project Scientist and the Lead of the Computational Arctic Team. His primary research area is modeling subsurface hydrothermal processes and earth system models at different scales and resolutions from site-specific to global scale. He uses numerical models to better understand physical signals contributing to changing climate. Currently, Dr Jafarov is working on building a data assimilation framework aimed to reduce biases associated with carbon and methane fluxes coming from thawing permafrost.