High quality, reference measurements of chemical and physical properties of seawater are of great importance for a wide research community, including the need to validate models and attempts to quantify spatial and temporal variability. Whereas data precision has been improved by technological advances, the data accuracy has improved mainly by the use of certified reference materials (CRMs). However, since CRMs are not available for all variables, and use of CRMs does not guarantee bias-free data, we here present a recently developed Matlab toolbox for performing so-called secondary quality control on oceanographic data by the use of crossover analysis. This method and how it has been implemented in this toolbox is described in detail. This toolbox is developed mainly for use by sea-going scientists as a tool for quickly assessing possible bias in the measurements that can-hopefully-be remedied during the expedition, but also for possible post-cruise adjustment of data to be consistent with previous measurements in the region. The toolbox, and reference data, can be downloaded from the Carbon Dioxide Information Analysis Center (CDIAC): http:// cdiac.ornl.gov/ftp/oceans/2nd_QC_Tool_V2/.Chemical and physical hydrographic measurements in the ocean have a long history during which the quality of the measurements have, in general, increased with time. With the quality of a measurement we mean both the precision and the accuracy; the latter being of great importance for inter-comparability of measurements conducted by different research teams, and for the quantification of temporal and spatial variability or trends. The accuracy of measurements can be increased by the use of certified reference materials (CRMs) as is common practice for carbonate system measurements and salinity. For instance, the introduction of CRMs for dissolved inorganic carbon (DIC) and total alkalinity during the WOCE period practically eliminated cruise-to-cruise biases in these parameters (e.g., Johnson et al. 1998). However, CRMs are not available for all variables or used on each cruise and measurements performed without the aid of CRMs are more prone to show biases, although the use of CRMs is no guarantee for accurate measurements as several factors can lead to biases, such as incorrectly quantified standard concentrations, the CRM concentration range being different from the samples, or other analytical difficulties. Overall, improvements in the instrumentation has reduced the achievable precision to about 2 lmol kg 21 for DIC and, with the use of CRMs, an accuracy better than 5 lmol kg 21 can be routinely obtained. We strongly recommend using CRMs whenever possible for your measurements, to increase the accuracy of oceanographic data, and for facilitating detection and quantification of trends. One way of verifying the accuracy of measurements conducted during an oceanographic cruise is by so-called secondary quality control (2 nd QC). It is important to note that 2 nd