Introduction

The resolution of bottle data is low compared to CTD data. Whereas some parameters are normally measured from every bottle (e.g. nutrients), the measurements of other parameters are to cumbersome or take to much time so that this parameters can only be measured every second or third station/bottle and therefore have even a lower resolution. To get profiles the bottle data can be interpolated using pressure. Or, to plot a section, be gridded using distance (or latitude/longitude) and pressure (or density, depth). Such interpolations do not make use of the information from other measured parameters. The MLR method presented here, uses this information and can reduce the interpolation error and can even be used to infer missing parameters or depict temporal trends.