Journal
CLIMATE DYNAMICS
Volume 39, Issue 6, Pages 1349-1371Publisher
SPRINGER
DOI: 10.1007/s00382-011-1196-9
Keywords
Arctic melt-season transitions; Atmosphere-sea ice interactions; Surface energy budget; SHEBA data; Arctic synoptic events
Categories
Funding
- National Science Foundation [OPP-97-01766, ARC0714053, ARC1023366]
- Directorate For Geosciences
- Division Of Polar Programs [1023366] Funding Source: National Science Foundation
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Various measurements from the Surface Heat Flux of the Arctic Ocean (SHEBA) experiment have been combined to study structures and processes producing the onset and end of summer melt over Arctic sea ice. The analysis links the surface energy budget to free-troposphere synoptic variables, clouds, precipitation, and in-ice temperatures. The key results are (1) SHEBA melt-season transitions are associated with atmospheric synoptic events (2) onset of melt clearly occurs on May 28, while the end of melt is produced by a sequence of three atmospheric storm events over a 28-day period producing step-like reductions in the net surface energy flux. The last one occurs on August 22.; (3) melt onset is primarily due to large increases in the downwelling longwave radiation and modest decreases in the surface albedo; (4) decreases in the downwelling longwave radiation occur for all end-of-melt transition steps, while increases in surface albedo occur for the first two; (5) decreases in downwelling shortwave radiation contribute only to the first end-of-melt transition step; (6) springtime free-tropospheric warming preconditions the atmosphere-ice system for the subsequent melt onset; and (7) melt-season transitions also mark transitions in system responses to radiative energy flux changes because of invariant melt-season surface temperatures. The extensive SHEBA observations enable an understanding of the complex processes not available from other field program data. The analysis provides a basis for future testing of the generality of the results, and contributes to better physical understanding of multi-year analyses of melt-season trends from less extensive data sets.
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