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Award Abstract #0632131
IPY: Collaborative Research: A Prototype Network for Measuring Arctic Winter Precipitation and Snow Cover (Snow-Net)
| NSF Org: |
ARC
Arctic Sciences Division
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| Initial Amendment Date: |
March 13, 2007 |
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| Latest Amendment Date: |
February 4, 2008 |
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| Award Number: |
0632131 |
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| Award Instrument: |
Interagency Agreement |
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| Program Manager: |
Neil R. Swanberg
ARC Arctic Sciences Division
OPP Office of Polar Programs
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| Start Date: |
March 15, 2007 |
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| Expires: |
February 28, 2009 (Estimated) |
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| Awarded Amount to Date: |
$420507 |
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| Investigator(s): |
Matthew Sturm matthew.sturm@usace.army.mil (Principal Investigator)
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| Sponsor: |
Department of Army Cold Regions Research & Engineering Lab
72 Lyme Road
Hanover, NH 03755 603/646-4219
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| NSF Program(s): |
AON IMPLEMENTATION
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| Field Application(s): |
0311000 Polar Programs-Related
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| Program Reference Code(s): |
OTHR, 5295, 1079, 0000
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| Program Element Code(s): |
5293
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ABSTRACT
A prototype international network is proposed to measure snowfall and ground snow at 5 arctic sites concurrently in an effort to improve the ability to monitor. All of the sites have been identified as key locations in a pan-arctic monitoring network and will augment existing meteorological and snow measuring instrumentation with solid-state snow pillows, heated plate precipitation sensors, snow fences, and eddy correlation towers for computation of sublimation. Ground surveys will also be conducted for snow cover depth, water equivalent, and other properties using tools that allow rapid collection of extensive data. These will be augmented with aerial photography and airborne remote sensing from inexpensive platforms (kites and UAVs) to visualize drift and deposition patterns. The combined suite of instruments and measurements is designed to allow closure of the winter water balance at each site, for the first time balancing the precipitation with measured accumulation. Using a set of modeling tools (e.g., a melt model, and a transport model for blowing snow), the PI's will a) develop methods and algorithms for quality checking both meteorological and snow data by cross-comparison between sensors and instruments, b) close the water balance in a way that produces more accurate values of winter precipitation and snow on the ground than are currently being collected, and c) apply a methodology to historical data from the existing gauge network to produce better estimates of past trends.
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