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Constraining Greenland's Surface Mass Balance using an Aggregated Dataset for Community Use


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Computer science & e-learning

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The accelerating loss of ice from the Greenland ice sheet is a major contributor to sea level rise. Recent increases in ice loss are attributed to changes in snowfall and melt water processes occurring over the surface of the ice sheets, termed surface mass balance (SMB) processes. This project enables the generation of new scientific knowledge regarding the state and fate of the Arctic environment by providing researchers access to an aggregated dataset of SMB measurements over both land ice in Greenland and Arctic sea ice. This dataset will enable better predictions of sea level rise and Arctic sea ice loss by validating models, improving remote sensing algorithms and providing a single dataset with field measurements for broad use within the polar science community. This project supports education by employing and training a student at the University of Colorado to understand SMB processes and methods for using measurements to constrain model predictions of Greenland ice mass loss. This project will support broad public education by contributing to the National Snow and Ice Data Center’s Greenland Today blog posts that update the public on the current changes occurring over the Greenland ice sheet. The goal of the project is to construct an aggregate dataset of field measurements that are consistent in format, properly described, and can easily be used to assess Greenland’s ice sheet mass balance. Without a common, usable, centralized dataset, important research is slowed down by unnecessary data discovery, access, and manipulation work currently being repeated by many different researchers around the country and internationally. Better prediction of sea level rise should not be hindered by this inefficient process. This research addresses the Polar Cyberinfrastructure’s call for long-term sustainable curatorship, standardization, management and discovery of data, and metadata and access and interoperability of data across scientific disciplines. This research seeks to answer and meet the following Scientific Questions and Cyberinfrastructure Objectives: Science Question 1. What is the current spatial and temporal resolution of existing measurements and how well can they constrain SMB model outputs? Science Question 2. Where and what type of SMB measurements are needed to monitor and further constrain SMB estimates into the future; Cyber Objective 1. To ingest measurements quickly into an aggregated, standard dataset for use by the Polar Science community; Cyber Objective 2. To create data protocols and community guidelines to expand the utility of specific geophysical measurements necessary to constrain SMB models and develop remote sensing algorithms.