The use of density surfaces in the analysis of oceanographic data and in models of the ocean circulation is widespread. The present best method of fitting these isopycnal surfaces to hydrographic data is based on a linked sequence of potential density surfaces referred to a discrete set of reference pressures. This method is both time consuming and cumbersome in its implementation. In this paper the authors introduce a new density variable, neutral density γn, which is a continuous analog of these discretely referenced potential density surfaces. The level surfaces of γn form neutral surfaces, which are the most appropriate surfaces within which an ocean model’s calculations should be performed or analyzed. The authors have developed a computational algorithm for evaluating γn from a given hydrographic observation so that the formation of neutral density surfaces requires a simple call to a computational function. Neutral density is of necessity not only a function of the three state variables: s... Abstract The use of density surfaces in the analysis of oceanographic data and in models of the ocean circulation is widespread. The present best method of fitting these isopycnal surfaces to hydrographic data is based on a linked sequence of potential density surfaces referred to a discrete set of reference pressures. This method is both time consuming and cumbersome in its implementation. In this paper the authors introduce a new density variable, neutral density γn, which is a continuous analog of these discretely referenced potential density surfaces. The level surfaces of γn form neutral surfaces, which are the most appropriate surfaces within which an ocean model’s calculations should be performed or analyzed. The authors have developed a computational algorithm for evaluating γn from a given hydrographic observation so that the formation of neutral density surfaces requires a simple call to a computational function. Neutral density is of necessity not only a function of the three state variables: s...