The use of density surfaces in the analysis of oceanographic data and
in models of the ocean circulation is widespread. The present best met
hod of fitting these isopycnal surfaces to hydrographic data is based
on a linked sequence of potential density surfaces referred to a discr
ete set of reference pressures. This method is both rime consuming and
cumbersome in its implementation. In this paper the authors introduce
a new density variable, neutral density gamma(n), which is a continuo
us analog of these discretely referenced potential density surfaces. T
he level surfaces of gamma(n) form neutral surfaces, which are the mos
t appropriate surfaces within which an ocean model's calculations shou
ld be performed or analyzed. The authors have developed a computationa
l algorithm for evaluating gamma(n) from a given hydrographic observat
ion so that the formation of neutral density surfaces requires a simpl
e call to a computational function. Neutral density is of necessity no
t only a function of the three state variables: salinity, temperature,
and pressure, but also of longitude and latitude. The spatial depende
nce of gamma(n) is achieved by accurately labeling a, global hydrograp
hic dataset with neutral density. Arbitrary hydrographic data can then
be labeled with reference to this global gamma(n) field. The global d
ataset is derived from the Levitus climatology of the world's oceans,
with minor modifications made to ensure static stability and an adequa
te representation of the densest seawater. An initial field of gamma(n
) is obtained by solving, using a combination of numerical techniques,
a system of differential equations that describe the fundamental neut
ral surface property. This global field of gamma(n) values is further
iterated in the characteristic coordinate system of the neutral surfac
es to reduce any errors incurred during this solution procedure and to
distribute the inherent path-dependent error associated with the defi
nition of neutral surfaces over the entire globe. Comparisons are made
between neutral surfaces calculated from gamma(n) and the present bes
t isopycnal surfaces along independent sections of hydrographic data.
The development of this neutral density variable increases the accurac
y of the best-practice isopycnal surfaces currently in use but, more i
mportantly, provides oceanographers with a much easier method of fitti
ng such surfaces to hydrographic data.