英文摘要: | The ongoing contribution of the Greenland Ice Sheet (GIS) to sea level rise is of continuing interest to the scientific community, policymakers, and the population at large. Geodetic determination of ice sheet mass loss is at the center of research on GIS contributions to sea level rise. There are many means for determining mass loss, but almost all rely on some form of satellite positioning, generally using the Global Navigation Satellite System (GNSS) or its subset Global Positioning System (GPS). The goals of the workshop are to 1) determine the community need for the current GNSS observation network in Greenland, 2) outline the science requirements for the network design, 3) define the path forward for the existing GNSS network, and 4) identify improvements to the existing network that will benefit the broader science community. Per broader impacts, the workshop will bring together investigators using data produced by the current network along with potential new investigators who can make use of GNSS network data. The workshop conveners plan to recruit participants from a spectrum from junior to senior scientists, and increase the diversity of the workshop participants wherever possible, by including funded invitations.
The objective of this workshop is to convene a 1.5 day workshop at NASA Goddard Space Flight Center in January 2017, with the purpose of defining a path forward for a Global Navigation Satellite System (GNSS) observation network in Greenland. The workshop will be held in conjunction with the 2017 NASA PARCA (Program for Arctic Regional Climate Assessment) Meeting. The goals of the workshop are to elucidate the current state of the GNSS network, illustrate the current uses of the network data (e.g., geodesy, crustal deformation, atmospheric modeling, space weather) and identify potentially new uses of the data, and determine the optimal configuration of the network moving forward (e.g., the ideal number of stations, the placement of stations, the replacement and upgrade of stations, and data management). |