Global relationships of the inherent optical properties of the oceans
被引:77
作者:
Barnard, AH
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机构:
Oregon State Univ, Coll Ocean & Atmospher Sci, Corvallis, OR 97331 USAOregon State Univ, Coll Ocean & Atmospher Sci, Corvallis, OR 97331 USA
Barnard, AH
[1
]
Pegau, WS
论文数: 0引用数: 0
h-index: 0
机构:
Oregon State Univ, Coll Ocean & Atmospher Sci, Corvallis, OR 97331 USAOregon State Univ, Coll Ocean & Atmospher Sci, Corvallis, OR 97331 USA
Pegau, WS
[1
]
Zaneveld, JRV
论文数: 0引用数: 0
h-index: 0
机构:
Oregon State Univ, Coll Ocean & Atmospher Sci, Corvallis, OR 97331 USAOregon State Univ, Coll Ocean & Atmospher Sci, Corvallis, OR 97331 USA
Zaneveld, JRV
[1
]
机构:
[1] Oregon State Univ, Coll Ocean & Atmospher Sci, Corvallis, OR 97331 USA
来源:
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
|
1998年
/
103卷
/
C11期
关键词:
D O I:
10.1029/98JC01851
中图分类号:
P7 [海洋学];
学科分类号:
0707 ;
摘要:
We have collected data during eight separate research cruises from open ocean to estuarine oceanic environments. Inherent optical property data collected during these cruises were incorporated into a large database totaling 1914 vertical samples. The range of each inherent optical property within this database spans over 2 orders of magnitude. Using this database, we examine the spectral relationships of each of the inherent optical properties based on the measurements made at 488 nm. The results of this study show that there are dependencies in the individual inherent optical properties (IOP) spectra that are linearly related. The information from the regression models is used to explain the linear dependencies observed in the global data set. A separate data set collected from a recent cruise is used to compare regional relationships with the global. The implication of this research is that over a diversity of oceanic regimes, there are fundamental, first-order relationships in the individual IOP spectra. These relationships can provide an estimate of the individual IOP spectral relationships when no information about the IOP is available, as is often the case in ocean color remote sensing. More detailed models, however, may be necessary in order to more accurately predict the IOP spectral relationships on regional scales where the expected range of variability is small.