Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
40 - ''-~¢ -(- 4~ fat ~ ~ ::: FIGURE 1.1 Location of primary (~) and secondary (x' stations versus estimates of vertical crustal motion for the period 1000 to ESTIMATES OF RELATIVE SEA-LEVEL CHANGE: KEY STATION APPROACH Methods One approach to estimating change in global RSL is to analyze data from key stations, arguing that changes at these stations are representative of changes in RSL in large (1000+ km) regions surrounding the stations. Ex- amples of such analyses are found in Table 1.1 (e.g., Fairbridge and Krebs, 1962; Barnett, 1983a). The latter work is summarized here. The use of the key station approach imposes the follow- ing series of constraints on the data to be analyzed. 1. High-quality, continuous measurement that reveals no sudden shifts suggestive of station movements should be used. The records should be as long as possible. 2. Station locations should be away from areas of strong tectonic movement (e.g., separated from areas of major deposition/uplift). 3. Stations should be unaffected by spurious physical TIM P. BARNETT - -_ ~_-~_ 12 ~_ TO -2; ~ ~ ~~ _~1 ~ ~- 1000-2000 yr BP `~;] J.~'\-\\ WAX ~ ) 1 I' / _ 2000 yrBP. Contours are in millimeters per year. After Newman et al. (1980). processes (e.g., gauge exposed to strong freshwater inva- sions). 4. The spatial density of stations by oceans should be proportional to the relative areas of the respective oceans, e.g., 2.4/1.5/1.0, for the Pacific/Atlantic/Indian (cf. Sverdrup et al., 1942~. The stations should be synchronous in time. Such a distribution will allow equal weight to be given to all oceans and years in the subsequent analysis, thereby avoiding biasing problems. 5. Finally, the selected stations must represent large . . . geographic regions. The locations of a set of stations that generally satisfy these criteria are shown in Figure 1.1 and are listed in Table 1.2. A method of inferring, quantitatively, the existence of a signal that is coherent over all portions of a data field using empirical orthogonal function (EOF) analysis (cf. Backus and Preisendorfer, 1978; Barnett, 1978) was ap- plied to the primary key station set and to the secondary station set to check sensitivity of the results to data pertur- bations. The sea-level data at position i are represented by