Statistics and Physical Oceanography (1993) / Chapter Skim
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1: Overview
1: Overview
Pages 1-16
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From page 1... ...
Statistical techniques have always been important in the analysis of oceanographic data. With the recent introduction of oceanographic observational mechanisms that yield much larger quantities of data than ever before, statistical considerations have gained even more prominence in oceanographic research contexts.
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From page 2... ...
It should be emphasized at the outset that statistical analyses of physical oceanographic data have not been developed in total isolation from developments in the field of statistics. On the contractor, statistical techniques are already used to an unusual degree of sophistication compared with their use in some other scientific disciplines, partly because of the need to develop techniques to understand the almost overwhelming quantity of observational data available.
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From page 3... ...
. Oceanography—A Brief Sketch The birth of oceanography as a science can be traced back to 1769, when Benjamin Franklin contributed significantly to scientific knowledge of the oceans by charting sea surface temperature in the North Atlantic and noting that the maximum flow of the Gulf Stream (which had been known to exist and had been used for navigation for a long time)
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From page 4... ...
Multiship surveys and repeated hydrographic surveys conducted beginning in the 19SOs and moored current meter and surface drifter measurements beginning in the 1960s revealed considerable spatial structure and temporal variability that did not support the view of ocean currents as simple and large scale. Much of modern oceanographic research has focused on understanding the nature of the rich spatial and temporal vanability through a proliferation of new measuring and modeling techniques.
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From page 6... ...
+ v Vv ~ 2n x v = g - _Vp + vV2v, p (1.1) where v is the three-dimensional vector velocity, V is the vector gradient operator along the x, y, and z coordinate axes with respective velocity components u, v, and w, n is the angular velocity vector of the rotation of Earth, g is the gravitational acceleration, p is the water density, p is pressure, and v is the molecular viscosity.
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From page 7... ...
However, the boundary and initial conditions have a random character, which imparts a randomness in the physical modeling. It is noteworthy that many of the methods used to determine the ocean circulation are based on measurements of various natural and anthropogenic chemical tracers.
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From page 8... ...
Moreover, the particular choice of turbulent mung coefficient depends critically on the spatial scales represented within the model. From coarsely spaced observations, it is even possible for turbulent transport to be counter-gradient (i.e., effectively a negative turbulent mixing coefficient, corresponding to energy transfer from eddies to the mean flow; see Starr, 1968)
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From page 9... ...
As discussed in Chapter 5, physical oceanographic research would benefit greatly from improved methods of visualization to examine the four-dimensional output of numerical models of ocean circulation. Besides the difficulties associated with the subjective natures of the choice of grid resolution, parametrization of turbulent viscosity, and the problem of availability of computer resources, another major issue in physical modeling of the ocean is assessment of the accuracy of the solution.
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From page 10... ...
In this context, then, even the output of a numerical ocean model forced by wind fields derived from in situ or satellite observations can be, and sometimes is, referred to as "data" by an investigator interested in analyzing the model output to study ocean dynamics. An important element of these multiple levels of transformation is that it becomes progressively more difficult, and sometimes even impossible, to quantity uncertainties in the output product.
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From page 11... ...
. An extreme example is the output of a numerical ocean circulation model forced by wind fields derived from a level-3 wind product.
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From page 12... ...
Most oceanographic applications of scatterometer observations require gncicled fields of vector winds or some higher-level wind product derived from Earth-Iocated individual vector wind "data." These fields are obtained by space-time averaging or interpolation and are generally referred to as "data" by investigators who analyze the wind fields or use them to force ocean circulation models. Example 2: Measurements of temperature and salinity by a conductinly-temperature-depth (CTD)
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From page 13... ...
These sections or maps are often referred to as "data" by investigators who analyze them or use them to force ocean circulation models or to verify ocean model output. Because of the multiple scales characteristic of both spatial and temporal variability in the ocean as discussed in Chapter 2, oceanographic data are commonly undersampled in several respects.
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From page 14... ...
. Even a Midyear record (which is unusually long for physical oceanographic data)
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From page 15... ...
Because of the variety of sampling problems inherent in oceanographic data, the term "noise" is often used to refer to more than just the measurement error associated with inaccuracies in the observations. Inadequately resolved contributions to a measurement from geophysical variability of the quantity of interest are generally referred to as "geophysical noise." As discussed above, such unresolved geophysical variability can arise from use of a discrete sample interval (aliasing)
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