Visiting Postdoctoral Researcher
Chen Zhang is a postdoctoral researcher at NSIDC and a visiting postdoctoral fellow at the Cooperative Institute for Research in Environmental Sciences (CIRES) at the University of Colorado Boulder (CU Boulder). Before joining CU Boulder, she did her Ph.D. in the Department. of Earth, Atmospheric, and Planetary Sciences (EAPS) with Wen-wen Tung (EAPS) and William S. Cleveland (Department. of Statistics and Computer Science) at Purdue University. At Purdue, she focused on the transdisciplinary projects that require deep analysis of big datasets by using advanced computational and statistical skills combined with Earth system science knowledge. Her Ph.D. dissertation is to study the Atmospheric Rivers (AR) in the United States and the Arctic. Chen applied a data-driven approach by developing an algorithm combining different factors, image processing, and advanced statistical methods to create large ensembles of AR indices to solve problems, aided by detailed data visualization and the knowledge of atmospheric dynamics. The systematic ensemble approach was made possible by distributed parallel computing with data and the divide-and-recombine approach using the R-based DeltaRho software back-ended by a Hadoop system. The generation of ensemble AR indices contributed to the 162 out of 198 international Atmospheric River Tracking Method Intercomparison Project (ARTMIP) Tier 1 Catalogues listed as “Purdue” Data.
Atmospheric rivers (AR) are one conspicuous pathway for poleward moisture transport from lower latitudes. They have been known to influence Arctic warming and sea ice decline in the boreal winter. Likewise, cyclones play an important role in the Arctic climate: Arctic cyclones strongly interact with the diminishing sea ice. While over the Arctic, the dynamic and physical process of how Arctic cyclones influence ARs and the associated sea ice effects are still missing in scientific literature. Chen Zhang will work with John Cassano, Mark Serreze, and Matthew Shupe use reanalysis and Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign data. The resarch aims to provide a comprehensive dynamic/thermodynamic analysis to quantify the influence of Arctic cyclones’ dominant physical factors on ARs and the associated sea ice evolution via the subsequent surface radiative budgets. Such physical understanding will lead to improved cyclone and AR predictions in the changing climate and bridge a knowledge gap in Arctic amplification.