Abstract
The in situ surface marine climate observing system includes contributions from several different types of observing platforms. Most observations come from mobile platforms, e.g. ships or surface drifting buoys. Climate applications using marine observations often require fields of environmental parameters to be constructed on regular spatiotemporal grids. User requirements are therefore typically presented in terms of parameter uncertainty at particular space and timescales. It is therefore important to relate the characteristics of marine observations, in terms of their expected quality and sampling distribution, to these requirements. A simple method to estimate the instrumental uncertainty in fields derived from a mixture of observation types is presented. This method enables preliminary assessment of the extent to which the available observations meet the stated user requirements. Example observing system adequacy assessments are presented for two climate variables, sea surface temperature ( SST ) and marine air temperature ( MAT ) using in situ data. The method is also applicable to gridded data sets constructed from combined in situ and satellite data. While the global metrics for SST show an improvement in observing system adequacy over time, the adequacy for MAT is declining. The assessments can determine the most efficient approach to improving observing system adequacy. For in situ SST the best approach would be to increase the number of different platforms making observations. For MAT , increasing the number of observations overall, regardless of platform and increasing the geographical coverage is required to reduce the uncertainty. The assessments would be improved by more extensive evaluation of uncertainties associated with each different variable for each platform type. It would also be beneficial to review the completeness of the user requirements: e.g. to include user requirements relating to the stability of averages on large space and timescales required for climate monitoring, or for constructing estimates of air–sea exchange.