期刊
CLIMATE DYNAMICS
卷 39, 期 6, 页码 1349-1371出版社
SPRINGER
DOI: 10.1007/s00382-011-1196-9
关键词
Arctic melt-season transitions; Atmosphere-sea ice interactions; Surface energy budget; SHEBA data; Arctic synoptic events
资金
- National Science Foundation [OPP-97-01766, ARC0714053, ARC1023366]
- Directorate For Geosciences
- Division Of Polar Programs [1023366] Funding Source: National Science Foundation
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据