Project Title: Collaborative Research: Linking sea ice and snow cover changes to Greenland mass balance through stratospheric and tropospheric pathways (Award# 1901603)
PI:Tedesco, Marco (firstname.lastname@example.org) Phone:(703) 292.7120 Institute/Department:City University of New York (CUNY), IPY Project? Funding Agency:US\Federal\NSF\GEO\OPP\ARC\ARCSS Program Manager:Dr. Gregory Anderson (email@example.com ) Discipline(s): |Cryosphere |Data Management |
Science Summary: Melting of the Greenland ice sheet is already the largest single contributor to sea level rise, and the rate of melt is accelerating. At the same time, the Arctic as a whole is experiencing unprecedented changes and setting new records, including the decline of Arctic sea ice cover, the decline and early snowmelt onset of Northern Hemisphere snow cover, and an overall warming at a rate more than double anywhere else on the planet. Studying and understanding the mechanisms linking the different Arctic components (Greenland, snow cover, and sea ice in the case of this research) and how, in turn, their changes are related to and driven by the atmosphere is fundamental to capture the physical processes driving the changes. This is, indeed, one of the key aspects to considerably improve our skills in estimating the future evolution of the Arctic under different warming scenarios and in projecting future sea level rise.
This research is quantifying the relationships between sea ice, snow cover, atmospheric circulation changes and mass changes over the Greenland ice sheet through a combination of observational and modeling tools. These include in situ observations of sea ice cover and snow extent as well as remote sensing products and estimates of atmospheric circulation changes and outputs from climate models. Researchers also use artificial intelligence (e.g., neural networks) to examine relationships between climate, atmospheric patterns and Greenland changes. Ultimately, this research is testing the hypothesis that atmospheric circulation changes associated with sea ice and snow cover extent variability control the mass balance of the Greenland ice sheet by modulating snowfall and surface melting. This research is also providing new insights on the linkages between the Arctic and mid-latitudes and how sea ice and snow cover changes might affect weather patterns outside the Arctic, including the United States.
Logistics Summary: This collaboration between Tedesco (1901603, LEAD, LDEO), Cohen (1901352, AER), and Mote (1900324, U of GA) will study, understand and quantify the relationships between sea ice, snow cover, atmospheric circulation changes and mass variability over the Greenland ice sheet by testing the following hypotheses:
1) reduced thickness and sea ice concentration during summer promotes the absorption of solar radiation by the exposed ocean with the stored heat released during fall (hence preconditioning the evolution of the atmosphere) and that early melt of sea ice and snow cover in the spring heats the high latitudes leading to a slowdown of the jet stream and amplifying midtropospheric waves affecting moisture transport and promoting more summer blocking conditions over the high latitudes
2) fall and winter sea ice concentration and snow cover extent affect stratosphere and mid-troposphere dynamics through the promotion of propagation of vertical waves that slow down the jet stream and promote blocking conditions over the Arctic during winter which persist into the warm season
3) atmospheric circulation changes associated with sea ice and snow cover extent variability control the mass balance of the Greenland ice sheet by modulating snowfall and surface melting
In order to test these hypotheses, researchers will use a suite of observational and modeling tools, including remote sensing and in situ observations of surface energy and mass balance components, sea ice cover and snow extent, remote sensing products, reanalysis estimates of atmospheric circulation changes and outputs from General Circulation Model(GCM) and regional climate model (RCM) simulations.
No fieldwork is conducted.
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